CA2906651A1 - Methods and systems for purposeful computing - Google Patents

Methods and systems for purposeful computing

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Publication number
CA2906651A1
CA2906651A1 CA2906651A CA2906651A CA2906651A1 CA 2906651 A1 CA2906651 A1 CA 2906651A1 CA 2906651 A CA2906651 A CA 2906651A CA 2906651 A CA2906651 A CA 2906651A CA 2906651 A1 CA2906651 A1 CA 2906651A1
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resource
user
percos
resources
information
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CA2906651A
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CA2906651C (en
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Victor Henry Shear
Peter Robert Williams
Jaisook Rho
Timothy St. John Redmond
James Jay Horning (Deceased)
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Advanced Elemental Technologies Inc
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Advanced Elemental Technologies Inc
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Abstract

A system, method, and computer-readable storage medium configured to facilitate user purpose in a computing architecture.

Description

DEMANDE OU BREVET VOLUMINEUX
LA PRESENTE PARTIE DE CETTE DEMANDE OU CE BREVET COMPREND
PLUS D'UN TOME.

NOTE : Pour les tomes additionels, veuillez contacter le Bureau canadien des brevets JUMBO APPLICATIONS/PATENTS
THIS SECTION OF THE APPLICATION/PATENT CONTAINS MORE THAN ONE
VOLUME

NOTE: For additional volumes, please contact the Canadian Patent Office NOM DU FICHIER / FILE NAME:
NOTE POUR LE TOME / VOLUME NOTE:

METHODS AND SYSTEMS FOR PURPOSEFUL COMPUTING
Related Applications This application claims priority to and is a continuation-in-part of U.S.
Patent Application No.
13/928,301, filed June 26, 2013, which is a continuation-in-part of U.S.
Patent Application No.
13/815,934, filed March 15, 2013, both of which are titled "PURPOSEFUL
COMPUTING" and both of which are incorporated herein by reference in their entirety.
BACKGROUND
Field of the Disclosure Aspects of the disclosure relate in general to computing architecture. Aspects include apparatus, methods and systems configured to facilitate user purpose in a computing architecture.
Description of the Related Art Computing has become deeply embedded in the fabric of modem society. It has become one of the most ubiquitous types of human resources, along with water, food, energy, housing, and other people. It interfaces in profoundly diverse ways with the pantheon of other human resources types ¨ it has become one of the two major doorways for human functioning, the other being direct physical interaction with tools, people, and/or the like.
Computing tools allow us to do many things that were unavailable - even unimaginable - not so many years ago, so much so that in recent years computing has become a binding foundation for the human community. It is used for administrating and operating a large portion of human infrastructure, for entertainment, socializing, communicating, sharing knowledge, and sharing between parties such as group members, friends, colleagues, community, and other affinity activities.

Most modern computer arrangements function as ubiquitous portals in a giant peer-to-peer Internet cloud. In the aggregate, along with the information they store and the real-time activities and the services they provide, today's computing arrangements can access and/or participate in a vast conglomeration of processing, storage, information, "experience," and communication resource opportunities. The reason we use these computers arrangements is to employ tools as means towards whatever ends we, individually and collectively, choose to pursue at any given moment ¨ that is we use computing arrangements to fulfill or otherwise satisfy our purposes. Fulfilling our purposes requires exploiting resources, and modern computing arrangements offer resource opportunities corresponding to a large portion of humanity's knowledge and expertise, as well as a virtually boundless variety of commercial, communication, entertainment, and interpersonal resources and resource combinatorial possibilities.
Altogether, modern computing, through both intranets and the Internet cloud, presents a huge, and from a human perspective, an unimaginably large, distributed array of candidate resources, relationships, and experience possibilities. This vast array, given its size, diversity, and global distribution, presents daunting challenges to fully, or even modestly, exploit, and no computing technology set provides reasonable ways for individuals or groups to see into the expanse of resource possibilities as they relate to anything other than their own highly specific areas of real expertise, except as to resources that may be materially, publically promoted.
Even experts, when operating in areas where their knowledge is incomplete, frequently have difficulty marshaling suitable best possible resource sets (set is at least one unit), particularly where the impetus for using resources is the pursuit, the acquisition of information and understanding.
Since, the very nature of computing's exploding web of resource opportunities is unprecedented and involves vast, unharnessed arrays of resources, much of this massive variety and population of items, locations, and potential combinations lies within a vast information fog.
2 SUMMARY
Embodiments include a system, device, method and computer-readable medium to facilitate user purpose in a computing architecture.
BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 is an example of purpose Domains with common members.
Figure 2 is an example of a user's resource selection.
Figure 3 is an illustrative example of resource interface.
Figure 4 is an example resource with opaque resource interface (e.g.laptop computer).
Figure 5 is an example resource with transparent resource interface.
Figure 6 is an illustrative example of an (NPR) interaction through PERCos resource interface.
Figure 7 is an example structure of a resource interface instance.
Figure 8 is an illustrative example of a PERCos purpose cycle.
Figure 9 is an example operating session embodiment (single session interface).
Figure 10 is an example operating session embodiment (multiple session interface).
Figure 11 is an example resource item.
Figure 12 is an example resource embodiment.
Figure 13 is an assimilation of non-PERCos resource into PERCos environment.
Figure 14 is part 1 of operating resource creation example 1.
3 Figure 15 is part 2 of operating resource creation example 1.
Figure 16 is steps 1 & 2 of operating resource creation example 2.
Figure 17 is step 3 of operating resource creation example 2.
Figure 18 is an illustrative example of a simplified resource created as a Construct instance.
Figure 19 is an example of a simple class system.
Figure 20 is an example simple class system, extended with mortal.
Figure 21 is an illustrative example of a simple Framework comprising resource elements specifications and PERCos resource interface specifications.
Figure 22 is an example resource with access through resource interface and a single resource element.
Figure 23 is an example resource with multiple resource elements, including component resources.
Figure 24 is an example transparent resource.
Figure 25 is an illustrative example of a resource relationship embodiment.
Figure 26 is an illustrative example of relationships between resources and PERCos i-Sets.
Figure 27 is an illustrative example of operating session comprising Framework and Foundation instances.
Figure 28 is an example PRMS instance hierarchy.
Figure 29 is an illustrative example of simplified resource management embodiment.
Figure 30 is an example of designator usage.
Figure 31 is an illustrative example of accessing resources using designators.
4 Figure 32 is an example of interaction between PIMS and resources.
Figure 33 is an example of an i-Set comprising information (e.g., query results) as an i-Element.
Figure 34 is an example of an i-Set created as resource.
Figure 35 is an illustration of interaction between PIMS, Resource Services, and Persistence Services.
Figure 36 is an illustrative example of Construct types including comprising resources.
Figure 37 is an example Framework Construct template.
Figure 38 is an illustrative example of a PERCos Platform Services embodiment.

Figure 39 is an example of PIMS structure for resource (R1).
Figure 40 is an example of PRMS interaction with Operating Session.
Figure 41 is an example of PRMS operating resource management.
Figure 42 is an example of resource services interactions.
Figure 43 is an example RMDF configuration.
Figure 44 is an example RMDF relationship.
Figure 45 is a simplified illustrative example of PERCos resource systems and service grouping.
Figure 46 is an example Resource Management Dynamic Fabric.
Figure 47 is an example Resource Management Assembly configuration.
Figure 48 is an illustrative example of resource assemblies.
Figure 49 is a simplified example of a Reservation Service embodiment.
Figure 50 is an illustrative example of resources and resource interface arrangements.
5 Figure 51 is a simplified example of resource component with multiple interfaces (e.g., disk/storage system).
Figure 52 is a simplified example of shared cloud resource showing separate i-element and multiple resource interfaces for a common cloud resource.
Figure 53 is a simplified example of shared cloud resource showing separate i-element and single resource interface controlling resource interactions.
Figure 54 is an illustrative example of resource comprising multiple types of resource elements including NPR and transformer.
Figure 55 is an illustrative simplified example resource.
Figure 56 is an example resource designator (i-element) hierarchy.
Figure 57 is an example of sharing resource arrangement information.
Figure 58 is an example hierarchy of PIMS.
Figure 59 is an example of an abstraction of a "generic" PERCos service structure.
Figure 60 is a simplified example of creation of resource from i-Set.
Figure 61 is an illustrative interaction between operating session and Resource Manager.
Figure 62 is a simplified illustrative example of processing of operating agreements.
Figure 63 is an illustrative example of states and state transitions four resource provisioning.
Figure 64 is an illustrative example of Construct usage.
Figure 65 is an illustrative example of construction evolution from templates to operating Construct.
Figure 66 is a simplified example of operating resources undergoing specification extraction.
6 Figure 67 illustrates example operating elements and/or data flow, PERCos and non-PERCos elements.
Figure 68 is a simplified example of a purpose class application organization.

Figure 69 is an example of concept mapping achieved through approximation.
Figure 70 is an illustrative example of Master Dimension embodiments.
Figure 71 are example metrics relationships.
Figure 72 are example resonance specifications.
Figure 73 is a mapping between the four types of purpose satisfaction metrics.
Figure 74 is an example commutative diagram.
Figure 75 is an example metrics calculation process.
Figure 76 is an illustrative example of a "generic" resource with interventions and interactions.
Figure 77 is an example resource relationship.
Figure 78 is an example of purpose Domain relationships.
Figure 79 is an illustrative example of Cred creation process.
Figure 80 is an illustrative example of dynamic Cred creation processes.
Figure 81 is an example of Cred elements and composition.
Figure 82 is an example of Cred elements embodiment.
Figure 83 is an example Cred publishing and associated processing.
Figure 84 is an example of three levels of Coherence interactions.
7 Figure 85 is an illustrative simplified example of PERCos SRO implementation processing and Coherence services interactions.
Figure 86 is an illustrative simplified example of Coherence Dynamic Fabric.
Figure 87 is an illustrative example of Coherence simulation embodiment.
Figure 88 is an example of Coherence Manager interaction with PERCos services.
Figure 89 is an example of Coherence Management configuration.
Figure 90 is an example Coherence management configuration with CDFs.
Figure 91 is an illustrative example of PERCos cycle processing showing example Coherence interactions.
Figure 92 is a distributed Coherence Management example.
Figure 93 is multiple users with a common purpose.
Figure 94 is multiple users with multiple operating contexts.
Figure 95 is an example of Coherence processes.
Figure 96 is an example Coherence management hierarchy.
Figure 97 is an illustrative example of computer Edge processing and Coherence processing.
Figure 98 is an example of Coherence interaction throughout the PERCos purpose formulation processing.
Figure 99 is a simplified PERCos cycle with Coherence processing.
Figure 100 is an example generalized SRO process flow with Coherence processing.
Figure 101 is an illustrative example of Coherence interactions with SRO
processing.
8
9 Figure 102 is an illustrative example of SRO specification processing and Coherence.
Figure 103 is an illustrative example of SRO resolution processing and Coherence.
Figure 104 is an illustrative example of SRO operational processing and Coherence.
Figure 105 is an illustrative example of Coherence Managers, operating agreements, and operating resources where Coherence Manager is a part of CDF.
Figure 106 is a simplified example of an embodiment of resource arrangements in the form of CDFs.
Figure 107 is an example Coherence Dynamic Fabric Manager.
Figure 108 is an example Coherence Manager Services embodiment.
Figure 109 is an example PERCos Evaluation Service instance.
Figure 110 is an example of Coherence template publishing.
Figure 111 is an example of a PERCos purpose cosmos.
Figure 112 is an example global purposeful network.
Figure 113 is an example interpretation/translation process.
Figure 114 is an example type 3 purpose expression processing.
Figure 115 is an example "generic" PERCos service.
Figure 116 is an example partial PERCos operating environment embodiment.
Figure 117 is an example shared contextual purpose experience session.
Figure 118 is an example of operating system dynamic Fabric configuration and interaction.
Figure 119 is an example user-related operating service configuration.

Figure 120 is an example user-related operating service configuration.
Figure 121 is an example user-related operating service configuration.
Figure 122 is an example UIDF and other dynamic fabrics interaction.
Figure 123 is an example UIDF and RDF interaction.
Figure 124 is an example of detailed view of SRO processing.
Figure 125 is an example of resource configuration at time Ti.
Figure 126 is an example of resource configuration at time T2.
Figure 127 is an example of resource configuration at time T3.
Figure 128 is a subgraph of an example class system relationship graph.
Figure 129 is an example knowledge extraction.
Figure 130 is an example of human-computer interaction.
Figure 131 is an example of a single user session PERCos architecture embodiment, including layered PERCos Core Services.
Figure 132 is an example of a shared networked experience session PERCos architecture embodiment.
Figure 133 is an illustration of example waypoints, resources, and descriptive CPEs.
Figure 134 are examples of universal class system.
Figure 135 is an example auxiliary category class system (WESN).
Figure 136 is an example auxiliary purpose class system (PWSA).
Figure 137 are example Construct templates for a class system editor.

Figure 138 is an example user characteristic faceting form including lists.
Figure 139 is an example faceting Purpose Class Application.
Figure 140 is a simplified block diagram of an exemplary embodiment of a PERCos environment.
DETAILED DESCRIPTION
A Purpose Experience Resource Contextual operating system/environment (PERCos) is in part about computing arrangement users connecting to a universal purpose-structured resource "network," a self-organizing grid infused with expertise and enabled by a universe of others, with all their respective nuances of expertise, capabilities, and knowledge and any associated tools and support services. This cosmos is a purpose-structured network for resource access and provisioning, for identifying and supporting specific purpose related and optimized resource instances. It includes, for example, users identifying very specific purpose application, environments, expert parties, and services, and with at least some embodiments supporting users gaining at least a portion of the expertise, capability, and/or knowledge inherent in such identified and deployed resources. This allows users to apply at least one or more portions of such expertise, capability, and/or knowledge to their purpose related processes.
PERCos (also called PERC) environments fundamentally differ from both current web technologies employing key word searching/retrieving for acquiring items and from semantically structured information stores. PERCos can rationalize, for example through the use of Coherence services sets, essentially inchoate/disordered distributed information and associated resource stores and instantiations, for example those comprising "big data," as well as a universe of computing users, user groups, other stakeholder parties, and enabling resources, such as hardware, software, and services, the foregoing collectively herein called Big Resource.

No current technologies, including for example implementations of semantically organized information stores, provide efficient, comprehensive, purpose matching resource identification and provisioning. Generally, current web technologies operate on descriptive information stored and associated generally within an item. Other than recommender information, such as Amazon's or Yelp's general rating systems, these systems generally characterize direct attributes of items, rather than provide organized insights into their one or more contexts of use by users. PERCos embodiments can "insightfully" map efficient, standardized expressions of user situational specific purpose related objectives described at least in part by prescriptive user Contextual Purpose Expressions to, for example, relatively corresponding contextual purpose characterizing, Quality To Purpose filtered, Stakeholder published descriptive Contextual Purpose Expressions, which such prescriptive and descriptive expressions may be transmuted through use of complementary profile, crowd history information, and/or other metadata. The contrast between existing technologies and PERCos is the difference between a not-organized-to-user priorities, optionally disparately tagged, inchoate distributed information mass of nearly boundless dimensions and diversity, to an efficiently structured, substantially standardized, and explicitly user purpose responsive, global information and related resources cosmos.
The human community is now entering an age where a form of pervasive connectedness is emerging. PERCos provides a deeply embeddable systematic way to harness such connectedness so as to be able to match our circumstances, as may be reflected by our purpose and contemporaneous context, with learning, knowledge, and discovery opportunities and methodologies. As in some PERCos embodiments, user and Stakeholder Contextual Purpose Expression of purpose approximations, when, for example, combined with purpose class arrangements, Repute Quality to (serving) Purpose and value infrastructure, PERCos Constructs, and Coherence services can readily connect users to resource opportunities that, by unfolding user inspection and evaluation and/or through the use of purpose neighborhoods and class and/or other grouping ontological and taxonomic arrangements, provides a setting for user learning and discovery and/or the like that enhances experience opportunities and general user productivity.
By providing a systematized environment supporting a purpose related cosmos, PERCos allows users to adjust to the approximate level of knowledge they have related to their purpose and navigate according to their awareness of purpose and their unfolding passage through any interim results to Outcomes.
Often people are aware that they need to learn, or discover, in order to achieve optimally practical satisfaction of a given purpose objective. Unfortunately, frequently people are unaware of the value of learning and discovery as relates to optimal fulfilling of their purposes.
Further, if people seek optimal resources and environments for purpose fulfillment, they will frequently find that tools to identify best specific to purpose resources are not available ¨ they are unable to associate and assess resources as they relate to very their specific current, personal purposes, though such best resources may be obscurely residing somewhere in the vastness of the internet. No general resource ecosphere exists for discerning specific purpose fulfillment contributing resources, and as such, no system invites parties to, in a systematic way, tailor resource sets to specific user purposes, that is align resources to the specific context and nature of user computing session or cross session specific objectives.
Many PERCos embodiments are designed to integrate purpose, experience, resources, and context into human-computer interactive operating environments, applications, devices, and/or the like, which are optimized to support Outcomes and interim processes that are directly responsive to user purpose specifications and associated contextual input.
These operating environments may be provided in the form of software operating systems/environments, software applications, device design, and/or the like which integrate into their design capabilities for user purpose responsive evaluation, management, and provisioning of resources and where such may be achieved through unified product design and/or through PERCos integration by use of APIs, plug-ins, and/or the like.

We live now live in a connected universe of billions of people and other resource items, and other than expense, efficiency, and accessibility, the only limitations in our deploying best available resources to satisfy a current purpose is sufficient knowledge or understanding of such possible, practical resources. While we are members of a vast population of connected parties and we have digital pathways to connect to nearly boundless resources, we are frequently applying far less than the optimal available resources to any given specific purpose than would be possible if we were better informed, that is had knowledge about, and practical access to, relevant, current purpose specific "best" resources.
Our processes in understanding and using resources towards a purpose satisfying outcome, whether social, entertainment, knowledge oriented, and/or commercial, are hampered by our absence, in any given instance, of, for most of our areas of activity, commanding expertise regarding the availability of resources, the arrangement of resources to our specific purposes, and, when applicable, the unfolding of a developing understanding related to our purposes, relevant resources and knowledge. If users could access any and all types and practical arrangements of resources in service of their differing, specific computing session purposes, if they could employ optimal selections of such resources and have access to expertise regarding such resources and/or their content and/or potential/capabilities, users could generally perform at much higher levels and have more satisfying results from their computing conduct. Computing users would find themselves far less frequently making do with a low quality of resources for a given purpose than fully informed individuals, and they would far less frequently find themselves trying to "reinvent the wheel."
Human activity choices and our knowledge of possibilities related to such opportunities seem to be at a crossroads, where now, at times a boundless array of resources may be utilized to satisfy purpose. Unfortunately, this relatively recent transformation from lives of relatively simple, basic activities, to lives where we can choose and manipulate resources to provide ourselves with better, quite specific results that are not simply tied to basic-short term survival, has not been matched with a general tool set systematizing and supporting human interface with purposeful possibilities regarding what we wish to accomplish at any given moment. Generally speaking, now that much human activity is funneled through computing arrangement interfaces, the unshackling of humans from a basic survival set of tasks to a vast set of human activity types and corresponding purposes has emerged without any systematization integrating the exploding number of possibilities and accordant resources. No formalized, interoperable frameworks for interfacing our purposes with optimum enabling resources and resource portions have arisen.
In part, this absence of focus on human resource and resource choice selection and provision systems may be due to the fact that the history of mankind has been mostly characterized by environments of relatively few and inherently relatively simple choices, whose complexity did not normally involve choices concerning resource selection from a significant number of possibilities, much less vast, disordered stores. But the human community is now experiencing a profound resource explosion and a need for a highly systematized, standardized choice assistance and knowledge enhancement system has rapidly arisen. PERCos inventions implement the first such set of embodiments enabled, in part by various embodiments supporting standardized purpose expression including, for example, Core Purpose and other Master Dimensions and Facets, purpose classes and neighborhoods, Repute purpose related Cred assertions and Effective Facts (EFs), purpose provisioning Constructs, and coherence evaluation and resolution, and/or the like. PERCos technologies can provide an integrated environment for choice and purpose unfolding, assisting users in the identification, evaluation, and use of resources from vast diverse store and producing optimum purpose responsive results.
Human choice should be based upon user purpose and relevant related context, further enhanced as desired by Quality to Purpose and related quality assertions as well as by combinatorial arrangements of resources that are responsive to specific user purpose computing environments (which may be arranged for ad hoc and/or persistent use). Such a general system for web based purpose management and fulfillment can substantially benefit from both an expertise based Quality to Purpose and related assertions architecture (Repute).
A purpose choice computing system can be optimized by purpose expression standardization for interoperable interpretation and efficiency, where such standardization is based at least in part upon higher level simplification principals, such as PERCos Master Dimensions and Facets, that support user ease in capturing/characterizing their purpose and related relevant context. The foregoing is important in reliable, efficient similarity matching between user purpose and resource store items, as well as to facilitate purpose responsive appropriate approximation results, such as purpose class(es) and/or other purpose neighborhoods and waypoints and/or sets of their members, which may be prioritized and otherwise evaluated based upon such purpose expressions, related context, and/or other metadata, and/or Boolean and/or other mixed or non-standardized user purpose expression components such as auxiliary Dimension elements. In managing a user's relationship to what appears to be boundless and often obscure resource opportunities, such purpose Dimension/Facet simplifications and other PERCos capabilities can bring users to purpose classes/neighborhoods for inspection and assessment and further filtering and evaluation, transforming, particularly in conjunction with Repute capabilities, a chaotic set of possibilities into a relatively informed set of candidates supporting an unfolding purpose development environment leading to more productive, valuable, and/or satisfying Outcomes.
The possible potential dimensions and nuances of resources are now highly varied, and can take a vast number of forms, and may, as they are pursued, branch and unfold in many differing ways. Both during free time and while working, many people could now enjoy or otherwise use a cosmos of resources, and users awareness of such resources may unfold over time, and collectively users and Stakeholders could self-organize resources and store or otherwise publish standardized and interoperable tools for Contextual Purpose Expression, resource profiling, purpose Coherence, resource prioritization, resonance purpose optimization, resource provisioning, resource class applications/Frameworks, and/or the like, all the foregoing supporting connecting users to a nearly boundless cosmos of other participants and resources for experience and other results fulfillment. Humans use computers to assist in realizing objectives.
PERCos formalizes the human/computer arrangement relationship as a partnership between human and machines, whereby users provide input specifically and in a formal manner, to direct machine operations towards supporting purpose Outcomes.
PERCos ¨ Purpose Experience Resource Contextual Operating System/Environment In some embodiments, a PERCos system is, in part, a network and/or local operating system, system layer, and/or cooperative one or more applications and/or services for purposeful computing. PERCos in part, extends traditional operating system capabilities for resource management by enabling user expression of purpose for selection of, and/or matching to, optimally useful purpose satisfying resources. PERCos in part employs means and methods for comparing Contextual Purpose Expressions (CPEs) prescribed by users to comparable Stakeholder published CPEs associated with resources, resource portions, and/or resource and/or purpose class published information. Such Stakeholder CPE information anticipates possible user purposes and related contextual information. PERCos resources, depending on embodiment, may be available locally and/or through/on one or more available networks, including for example, Cloud services.
With certain embodiments of PERCos users can interact with a global "purposeful network,"
and such network may, for example, encompass Big Data, users and user related groups, machines and devices, applications and other software, and local and cloud services, the foregoing comprising "Big Resource." PERCos resource elements, individually and/or in combination, represent resource sets that can be made available and/or otherwise proffered specifically in response to user expressed Contextual Purpose Expressions.
A PERCos system provides a network management platform for one-to-boundless computing.
That is, a user can potentially benefit from resources located anywhere, made available by anyone and in any simple to complex combination. For example, published materials, associated machines, devices, computer software, expert consultants, social networking companions, and/or other arrangements, including cloud services, might be used by anyone and/or any group, anywhere, in any allowable and/or operable user-selected combinations (subject to publisher and/or other Stakeholder restrictions and logical operational considerations). PERCos views computer operations as the interaction between users and their purpose related specifications and actions with computing arrangements, for example, for identifying, configuring, provisioning, and/or managing computer processing resources in a manner responsive to user purposes, that is PERCos employs an architecture that responds to user specifications and other purpose related input to effectuate purpose fulfillment processes.
In the evaluation and/or provisioning of purpose fulfillment related resources, PERCos, through the use of its evaluation, monitoring, conflict resolving, completion, and other capabilities, synthesizes operating specifications through, as applicable, the use of user and applicable Stakeholder purpose expressions and related specified and/or otherwise allowed further input information such as, for example, resource metadata information, user profile information, and exogenous societal regulations or other considerations.
Human-computer interaction involves a set of human experiences that unfold during sessions that are generated using specified and/or selected resources: computing hardware, software, data (for example, permutations of Big Data), sensors, machines and related processes, and/or possibly other users, altogether known in PERCos as Big Resource. Purpose specifications and/or comparable user actions normally provide the initial, interim, and/or Outcome input for PERCos sessions, and involve at minimum users providing initiating purposes.
Further, PERCos system, PERCos purpose specification, purpose class applications, purpose plug-ins, and/or similar arrangements, can guide both an evolving identification, selection, provisioning, and/or use of desired resources though interim purposeful user actions.
PERCos systems support both user ephemeral and Stakeholder declared purpose specifications, and, in various embodiments, associated purpose and resource related taxonomic and ontological arrangements. These purpose related, published or ephemerally declared arrangements are employed by users and PERCos for providing purpose satisfying outcomes, that is, purpose fulfilling computing session interim and/or culminating consequences.
Publishers publish PERCos resource arrangements and related, declared purpose specifications, which may take the form of one or more purpose class applications and declaration of purpose class memberships.
PERCos operating systems and/or layers alone and/or in conjunction with purpose class applications, application plug-ins, and/or API implementations and/or the like, can support user/computing arrangements that can then filter, identify, and prioritize, including qualitatively evaluate and provision, appropriate purpose fulfillment resource arrangements.
Provisioned PERCos resources and/or a PERCos implementation can operate and manage user/computing domain cross-Edge communications in support of unfolding resource/user interactions.
In particular, PERCos is by design a cross-Edge user/computing arrangement architecture that supports, assists, and transforms human approximate and relational specific purpose concepts into computing resource parsing, provisioning, and processing capabilities. In response to such relational thinking and at least in part to user specifications/selections, PERCos can seek and/or provision from Big Resource particularly applicable purpose satisfying resource sets as purpose and/or purpose class specific user/computer purpose session user outcome fulfillment tools.
Users rely on their inherent relational computing nature, the patterns people recognize through their foundation of experience, context, and memory. Computers employ a different class of operations: precise digital processes, processing arrangements, stored data, and any associated input/output. As applicable, PERCos capabilities, with or without direct user direction, can manage, filter, evaluate, organize, and/or provision computing arrangement resources into focused user purpose specific class applications, platforms, and/or other purpose fulfillment means that may operate on PERCos operating system and/or layer implementations, as well as on compatible computer applications which accept, for example, PERCos plug-ins and/or API
code additions. Further, PERCos can employ Constructs associated with purpose expressions, such as Frameworks, Foundations, resonance specifications, and/or the like, the foregoing having been formulated and adapted at least in part to facilitate optimal adjustment of various resources synthesized to an optimally purpose compliant operating specification set balance.
Such Constructs may specify "approximate" potential purpose associated PERCos session building blocks that contribute to the cohering of an optimally balanced purpose fulfillment operating specification set.
In some embodiments, PERCos systems support deploying resources in accordance with Contextual Purpose Expressions (CPEs), including for example Core Purpose specifications, augmented when applicable by Master Dimension and/or auxiliary specification information.
Such CPEs can enable:
(a) users to, for example, provide Contextual Purpose Expression and other input to identify, initiate, experience, provision, store, and/or publish computer sessions and session resources that provide the best fit for realizing specific user purpose Outcomes. This might include supporting user unfolding purpose expressions and system response processes, and when desired, specifying contextual simplification Dimension Facets. Such Dimension Facets, might be in an example, such as user is a beginner related to a specified purpose, unsophisticated related to the related purpose domain, wishes limited complexity relative to user sophistication, has a certain resource budget relative to one or more specified purposes and/or purpose classes within, for example, a time frame, and/or needs a purpose process not to approximately exceed 30 minutes.
(b) Stakeholders to, for example, publish information regarding resources, including associated Stakeholder declared descriptive CPEs, purpose class membership, and/or any related specifications, (e.g. specifications which may be similarity matched to user purpose specifications, where such Stakeholder specifications identify user purpose "sufficiently" corresponding, prioritized, and/or otherwise evaluated/filtered resource sets). Stakeholder may make Contextual Purpose Expressions including, in some embodiments, Dimension Facets specifying that a resource is intended for and/or may be related to one or more specified purposes, for example, designed for use by a sophisticated user, has a certain level of complexity relative to user sophistication level, and the like. Stakeholders may further make Stakeholder commercial and/or affinity group interest declarations declaring, for example cost to use, license rights, claimed quality of resource to specified one or more purposes, as well as sovereign government and/or other affinity group interests related to resources;
The foregoing may be complemented by any other information that in the used PERCos embodiment may be declared by Stakeholders and/or users. Appendix D represents an example embodiment of aspects of PERCos Formal resource publishing and related information, management, and purpose matching aspects.
PERCos, through its user/computer arrangement cross-Edge features and its various purpose support capabilities, helps resolve a primary current web resource usage challenge: user's inability to experience quality Outcomes to their underlying purposes, and in particular, users inability to identify quality and optimally productive user purpose fulfilling resource sets when such users lack a reasonable ability/knowledge base to frame their needs and characterize any associated requests. It is self-evident that such reasonable ability may be absent until developed and/or the user is otherwise supported. PERCos provides the innovative, supportive basis for such user framing, particularly in domains where users lack substantial command/experience/expertise. As a result, PERCos innovatively helps answer this current conundrum, the inability of users to reasonably frame requests for, and/or interact with, resources without sufficient relevant purpose domain related expertise. In such circumstances, users may lack necessary domain knowledge to effectively characterize their input and resource requests and they may be better served by a process approach where uses are presented with an approximate, purpose related resource neighborhood having resources that may be especially designed to support purpose knowledge enhancement and purpose related resource utilization and where such neighborhood resources may be identified, evaluated, filtered, prioritized, selected, and/or provisioned in a manner reflecting contextual purpose variable set matching and assessment processes. This challenge, the absence of user reasonable expertise (and which absence can include many variables such as information specifics, knowledge command over domain information, and user knowledge and command relating to the type, availability, and/or use of resources) is largely unresolved by currently available technologies that are unable to provide general systems for users' contextual realities and specific purpose orientation ¨ these systems fail to systematize resource availability and provisioning based upon purpose considerations, and they further fail to both practically convey effective expertise support adapted to specific current user purpose(s) and to support the knowledge and opportunity development processes idiosyncratically specific to differing user purposes.
In the face of the opportunities of Big Data and Big Resource, PERCos provides a broad based, practical, user ecumenical system for supporting user learning, discovery, resource provisioning, and resource use, including during session and/or cross session progressions that can leads to quality purpose fulfillment outcomes.

In most directed human activities, one or more explicit, articulable purposes underlie human actions and employment of resources. Satisfaction for participants in such activities normally results from either a perceived fulfillment of their initiating, underlying purposes, or the experiencing of sufficiently satisfying purpose related refinements, results, and/or associated experiences that evolve from such initiating purposes and processes. It seems evident that most individuals will experience or otherwise enjoy particularly satisfying computing session outcomes if their session specific computing resources are explicitly in alignment with their session computing activity purposes, and, in particular, if the "best of breed" applicable resources can be easily applied to fulfill the differing user purposes that occur at different times.
Clearly, the capacity to identify and provision resources that are specifically aligned to one's current purpose, and, particularly the capacity to apply the most productive and applicable of such possible/available resources, would have great value since such purpose-aligned resources, and in particular, those consistent with user purpose related context, would be most likely to produce optimal outcomes and optimal user satisfaction.
But, as computer users and their computing arrangements are now inhabitants within a nearly boundless web of Internet and intranet resources (including other users and their computing arrangements), the challenges in identifying optimal, specifically purpose matching resources and resource sets is a great unmet dilemma that requires new technology approaches. Since the most powerful computing arrangement would be one that is most responsive/satisfying of a user's current purpose, it would seem that this might be a priority of current computing architecture. But, in fact, there are no general-purpose purpose fulfillment architectures. This is likely due to the vastness of type and location of web resources and the inherent complexity in determining the simplifying organizing purpose related conceptual dimensions that might be employed to replace a chaotic resource universe with a coherent and efficiently operating resource cosmos.

The complexity in identifying purpose fulfilling web based resources and resource combinations, given today's nearly boundless array of intemet resource opportunities, types, locations, and qualities, is in part revealed by the clear absence of any formal system that enables consistent, straightforward, efficient, and reliable identification, categorization, evaluation, arrangement, provisioning, and support of user purpose resource sets. No current technologies enable the standardized specification and communication, relational approximation, identification, prioritization, cohering, and provisioning of specifically purpose aligned, purpose satisfying component resources. Further, no current system provides a sufficiently broad and unified view of both the nature of computing resources and the contextual perspectives necessary to optimally align resources to user intent.
Absent a well implemented general operating system, environment, layer and/or application means to associate resources with context specific, explicitly current, human purposes, identifying and applying web based resources to human purposes will remain fragmented, haphazard, and inefficient, that is often dysfunctional for many purposes.
This is particularly applicable where a user's expertise in identifying, assessing, combining, and/or provisioning resources are any less than highly expert. This absence of a general, formal means for identifying "unknown to user" resource opportunities in a manner specifically responsive to, and optimized for, user current purposes, means the rich, deep, diverse possibilities of web based resources are obscured behind a veil of seemingly boundless, largely undifferentiated as regards to purpose, objects and services. At least for the foreseeable future, crowd behavior and semantic web, as well as fragmented topic based expert systems and related tools that try to deconstruct existing web information into useful indicators of user behavior and relevance will not have the adaptive particularity and comprehensive reach provided by the contextual purpose inventions provided by PERCos implementations and described herein. Further, search and retrieval technologies such as Google and Bing search environments and/or the like will perform consistently/adequately only in circumstances where users can sufficiently, and explicitly, describe the information, information resource, or such sufficient portion of key information resource characteristics that prove adequate to the material to be retrieved, and satisfy such a limited, that is, specific purpose context. That is why these environments are often characterized as search and retrieval environments ¨ the user normally needs to know enough to specify what to retrieve, or at minimum to give a sufficiently relevant search specification to result in a drop-down suggestion that the user is sufficiently informed so as to select. While information resource management systems such as knowledge graph, clustering, and domain specific expert systems can provide users with some useful capabilities and guide posts when pursuing knowledge and discovery activities. These systems tend to be relatively inefficient and impractical and insufficiently adaptable to specific user contexts and user objectives as regards users fulfilling their active purpose set.
As the developed and developing world increasingly participates in, and connects through, an electronic web having associated vast, seemingly boundless quantities of information, software, services, and human and group inhabitants, existing resource access, search, classification, identification, evaluation, and provisioning tools are unable to, in an integrated, efficient, and optimizing manner, support users and user group resource requirements. Users inherently want to use resources for the most satisfying Outcome, that is those resources that would "best"
satisfy their current purpose(s). But current systems are not effectively responsive to individual and group current purpose needs since they lack any reasonable methods for user purpose specification enabling users to "outline" their objectives in a manner that efficiently leads to computing session specific resource sets, including supporting specific, specified purpose fulfillment "environments," where such systems are responsive to user purposes, that is user specific, current needs and objectives.
In particular, there are no general purpose technologies providing reasonable methods to correspond user specifications of specific, current user purposes with possible resources, including performing quality to specific user purpose prioritization, and/or provision of optimal quality to purpose resource sets. Rather, existing technologies constitute a balkanized array of tools, such as characterization and retrieval search engines, recommender systems, clustering and knowledge representation (e.g. graphing) tools, classifiers, encyclopedias, expert systems, and other piecemeal products and services.
People interface with the world around them through their senses. Such interfacing involves interacting with "resources," including, for example, relating to other people, using tools to fulfill tasks, and experiencing the modification or enhancement of knowledge through observation, evaluation, and/or absorption of information. For most of the history of mankind, users interacted with resources that were in the immediate proximity of some or all of the participating individuals. Indeed, until recently, physical realities limited the volume and diversity of resources that could, or would, be physically present for any individual or group of individuals at any given point in time, and resource users normally needed to be either physically proximate to resources, or use human "agents" who were physically proximate to such resources. Given this historical physical proximity limitation regarding the practical use of most resources, information systems for organizing, identifying, evaluating, prioritizing, provisioning, and using resources have generally reflected such physical proximity limitation solutions, they were primarily systematized based on categorization of the direct attributes of each constituent member, and such members were placed in organizational hierarchies, such as class systems, that could "hold" such members in consistent and normally non redundant places, such as stacks in a library.
Historically, normally, a library member, for example, was physically positioned in only one place in the system, and the quality of a member resource to a given purpose, and differing arrays of purposes, was not codified. Users, and/or a librarian or like agent, would physically access desired such resources by retrieving them from a specific library storage location. Such general purpose systems for such large scale library information resource organization, such as Dewey Decimal Classification or Library of Congress Classification, inherently lack the capacity for efficient identification and deployment of members in variety of different places that might correspond to respective differing use purposes, and they further fail to supply "reschufflable" purpose related combinatorial resource arrangements (for example, effectively mashable) that can supply user specific purpose (and/or purpose supporting) and/or purpose class fulfilling environments. As a result, such classical classification systems share, for example, deficiencies with search and retrieval systems. For example, they generally require a level of knowledge/expertise regarding the nature of potential resources in order to reasonably efficiently support a user's quest for purpose specific best available, or even applicable, specific resources. And such systems do not provide specific purpose adapted combinations of different resources where such resources are responsible for complementary/different/differing contributing resource subsystems that support a given purpose fulfillment environment, and where such resource subsystems can, for example, contribute to at least in part standardized, published purpose Frameworks where such resources fulfill, for example, differing specified operative roles.
As with such library classification systems, current computing technology does little to assist users in efficiently identifying and provisioning resource sets that are aligned to a specific user purpose current at a given time. Generally resource providers have a somewhat similar challenge. They have no systematized capacity to identify and provision potential users where their resources might be particularly useful in contributing to specific user purpose Objectives.
Such providers have no standardized, broadly interoperable arrangement by which to specify the appropriateness of their resources as tools that would contribute to optimal deployment and/or use of such resources for satisfying specific user computing session objectives.
Given substantial expertise relative to a current purpose, users may have the capacity to selectively identify, that is describe or point to, desired resources which they may then be able to retrieve and/or utilize. But regardless of whether any such user identified resources are functional for a given purpose, even with substantial expertise, users may indicate resources that are far less than optimal, given the massive resource diversity, including type, location, provider, timeliness of version, and explicit fit to specific purpose, that are now potentially available through web based computing. Further, for most objectives and topic areas, users have limited expertise ¨ generally an individual's true mastery of most subject areas is quite limited, and often far more limited than they realize. In the absence of expertise, resource retrieval technologies and resources are still utilized in attempted satisfaction of user purposes related to such areas, and most people quickly learn to live with the readily available and may treat such resources as adequate or otherwise serviceable. It is normally not clear to individuals -- in the absence of an understanding of available superior resources and PERCos new forms of (e.g.
mashable) contributing component resource organization means -- how profoundly many user purposes are under served by available computer tools. In fact such recognition would likely be, particularly for the average user, unproductive and unsettlingly frustrating since the journey to optimal resource identification and provisioning (when possible), can be too long and difficult a process using existing technologies.
Generally, in satisfying purposes through the use of resources materially involving learning and/or discovery processes, users need to be presented with appropriate resource environments and/or "evolving" differing resource set sequences versus "answers" or answer lists or knowledge graphs, such as available with search engines. Such learning and related environments enable user development of sufficiently meaningful representations of their specific desired purposes as they evolve their understanding towards a purpose fulfillment culmination or stopping point. Unfortunately, generally speaking, no architecture, no cosmos of technology and resource administration exists enabling the corresponding of computing resource sets and resource combinations to the often approximate nature of user usage purposes and their relevant contextual variables. Importantly, in pursuit of satisfaction of current purposes, users are frequently not seeking, or yet qualified to identify, specific purpose satisfying end results.
How do users, for example, efficiently search, if they are not sufficiently knowledgeable to identify that which they wish to retrieve? Instead, users need resources that are appropriate and tailored to their user circumstances and purpose needs and this can only be effectively, consistently achieved through a user purpose specifications process that is matched with one or more corresponding resource associated purpose specifications. Such a technology arrangement should support purposeful processes that unfold to results, either interim or final.
Appendix E represents a non-limiting example of an embodiment of resource types, contextual variables, and other inputs and attributes employed in metadata, purpose expression sets, and/or other PERCos specifications.
Given the nature of such unfolding user processes where users are developing and identifying purpose related results, users will often need to both declare and employ lossy approximating concepts such as specified by PERCos user purpose expressions, and employ PERCos and/or related application processes supporting a cross user/computing arrangement Edge where user experience reflects a progression of human relational thinking processes in response to an unfolding of resource supplied inputs that enable developing human knowledge/perspective. It should be noted that these processes normally, when users are in an at least in part learning mode, function most effectively when purpose class relational approximate information sets are employed, versus "precise" specific answers search engines, result lists, and/or, for example, knowledge graph and/or clustering groupings. While these tools might, under some circumstances, make a system seem responsive, they frequently provide the learning user with confusing, insufficiently informative, and/or damaging to user results.
Generally, the foregoing results, particularly in many learning and discovery contexts, in less than optimal efficiency, costs, relationships with resources (including other possible participants), levels of complexity, and reduction in confusion; they provide far less than efficient time use and productivity outcomes, and can fail to provide optimally enjoyable networking environments and experiences.
With PERCos (also called PERC), resource supplied learning/discovery inputs ¨
which in some embodiments can take the form of purpose neighborhoods for inspection/learning/evaluation processes by users ¨ can be made available through identifying user purpose specific resource sets or at least in part purpose resource set application environments, that can, in cross "Edge"
communication with users, present coherent purpose responsive results and/or purpose specific user interfaces and resource interaction supporting further purposeful steps that develop towards purpose fulfillment or closure.
In certain embodiments, two significant resource features supported by PERCos systems are:
1. Their ability to treat all types of PERCos deployable and published processing related information representing any computing session specifiable and interpretable capabilities as specifiable discrete resources, resource portions, and resource sets, which may or may not be further combinable. The foregoing includes, without limitation, devices through their data interfaces and specifications, network services, computational processes, specifications serving as interface information for humans and groups, for example as participant representations and associated data that may be operatively associated with cross-Edge interfacing, as well as communication channels, knowledge information sets, and any other type of processable data representing any type of information and/or "real-word" processing related capability, all the foregoing providing elements contributing information and/or processing and/or storage and/or communication for a PERCos session operations (including, for example control algorithms, and usage related information for machines and devices), such resources for example, including published information regarding and/or representing any resources external to PERCos which are treated as cross-Edge elements that communicate with, and/or receive communication from, PERCos, such as memories, microprocessors, databases, software, networks, cloud services, participant and Stakeholder representations, and the like.
2. Their ability to treat all such resources uniformly in accordance with purpose and any associated control specifications.

PERCos systems are substantially purposeful, user and Stakeholder specification-driven environments. Applicable specifications, received from user and/or machine input, support the two primary groupings of PERCos platform activities, (1) identifying, evaluating, selecting, and/or provisioning of resource sets, and (2) use of resources in service of expressed user purpose(s). PERCos can employ its operating platform components in combination with purpose related local and/or remote PERCos compliant resources and user instructions in preparation for, and/or provisioning of, purpose fulfillment platform/resource combinations.
Stores of PERCos compliant resources are partially or entirely purpose specification arranged (and may, for example, be complemented by traditional category classification) with the organizational objective of best satisfying user purpose(s) given possible and/or practical available resources. Users relate to resource information through their tendering and/or provisioning. PERCos resource information management is specifically adapted through the use of standardized and interoperable purpose expression capabilities, and in some embodiments, purpose class and/or other ontological and/or taxonomic capabilities, to provide specification tools to organize and identify purpose related resources that are specially adapted and/or useful for specific purpose fulfillment objectives. Resources may be assessed through such purpose related specifications, and, for example, through the use of coherence processes, and PERCos may process any resource set, at least in part in response to at least a portion of such purpose specifications, for example, PERCos resolves collective applicable specifications in a manner optimally consistent with user and/or published Stakeholder purpose specifications, including identifying and resolving coherence managed conflicts and/or deficiencies among resources and/or between, for example, user and Stakeholder specifications, and any other applicable specifications, so as to produce a co-adapted and consonant resource set.
As referenced earlier, PERCos employs Contextual Purpose Expressions as specifications declared by users to, at least in part, represent their purpose(s) for a given computing activity set.
Contextual Purpose Expressions are also employed by Stakeholders as purpose specifications associated with resources and resource and purpose classification groupings.
CPEs normally describe human purpose concepts in the form of lossy, relationally approximate, notional representations. Such representations are operatively used to identify resources that relatively align with user purpose fulfillment objectives, either generally/comprehensively and/or in the form of a component that can contribute to a given purpose fulfillment process. PERCos uses CPEs both to represent user and Stakeholder purpose related conditions/objectives, but also to characterize one or more purpose classes instances that are associated with such purpose specifications, so as to operatively organize and optimize resource identification efficiency, particularly when dealing with vast data stores, such as Big Data or more encompassing Big Resource. In such circumstances, purpose classes may contain resource sets as members whose membership, in certain embodiments hereunder, are declared by Stakeholders, with such membership being associated with any such resource and therefore such resource being associated with the one or more of the purpose classes associated Contextual Purpose Expressions. In these circumstances, any given purpose class can constitute a purpose "neighborhood" populated by such Stakeholder declared members (and/or by members specified as such as a result of historical usage associations and/or class attribute inheritance and/or other algorithm calculations). The declaration of resource sets as members of one or more purpose classes can support a two or more step process involving the generalization of bringing users to one or more purpose neighborhoods comprised of resource members, where such member resources, for example, can be further ranked, examined, filtered, selected from, organized into groups, and the like. This can profoundly simplify managing Big Data or Big Resource usage by inspecting, for example, an index for purpose expressions for, for example, tens of thousands of purpose classes to derive appropriate one or more approximation neighborhoods, and then, for example, if desired further processing neighborhood member associated purpose related specification information. This provides an alternative to examining, for example, an index for all resources, which might comprise billions, and ultimately trillions or more of resource items and their corresponding huge one or more indexes and/or other information manager tools. For example, in certain embodiments, PERCos user prescriptive purpose specifications can be similarity matched either directly against information store arrangements for published purpose expressions (with or without other purpose related information) associated with resources sets, or can be similarity matched against purpose class CPEs (with or without further examination or other use of purpose class metadata). More detailed filtering may take place in evaluating purpose class members by using, for example, resource metadata, PERCos value to purpose Repute system input (including Cred quality assertions, Effective Facts (EFs), and Faith Facts (FFs)), and/or associated user purpose expression secondary information (information specified or acquired at least in part for such further member based filtering).
PERCos combining of inherently lossy "approximate" purpose specifications prepared by both users and resource Stakeholders (e.g. providers, creators, Cred asserters, and/or other Stakeholders) can enable users to enter into learning, discovery, and/or experiencing processes that correspond to their inherently generalized purposes and at least in part support user passage through such learning, discovery, and/or experiencing processes to session or other process sequence culmination or termination. As discussed, PERCos means can also support users using, in combination with their Contextual Purpose Expressions, similarly approximate and lossy purpose cosmos organizing purpose classes, enabling vast and massively diverse resource sets to function as practical purpose resource stores that are optimized for user purpose fulfillment related user evaluation, interaction, and/or provisioning.
Elements from such resource stores can be practically matched and filtered and/or otherwise selected or filtered for their purpose fulfillment qualities. The efficiency and effectiveness of such purpose similarity matching processes can be potentiated in quality of Outcome through the use of Quality to Purpose Cred Repute processes that may further evaluate, prioritize, and/or provision resources, including performing such processes on resources specified as members of one or more appropriate purpose classes. Further, such resource stores can provide resources as building blocks for resource environments and other purpose frameworks, including purpose class applications, the foregoing in support of unfolding user purpose development and/or fulfillment processes.

PERCos provides a purpose expression architecture that operatively interacts with PERCos purpose related resource organization and resource provisioning (e.g.
Coherence and PERCos Constructs). Such PERCos purpose specifications involve standardized and/or otherwise interpretable descriptions of user objectives and related, particularly relevant conditions that provide information informing PERCos processes of user purpose, for example:
focus, context, and Quality to Purpose facets, the foregoing for calculating and/or otherwise identifying degree of match, and value of, resource sets to user purposes. In particular, PERCos purpose specification can employ combinations of one or more verbs and one or more categories and/or subcategories that together represent user Core Purposes that approximately correspond to the central focus set for user activity. Such one or more Core Purposes may be combined with particularly relevant user standardized or otherwise inter-operatively interpretable contextual variables such as: available PERCos Master Dimensions including specific budget(s); available time duration and/or specific time; user expertise relative to Core Purpose focus; desired complexity and/or "length" of resource material sets and/or portions thereof;
complexity and/or arrangement of interfaces; quality of experience variables; and any one or more characteristics regarding any expert and/or crowd and/or historical resource set(s), including any Repute assertions and/or derived values relevant to such resources and/or resource classes and/or the like. The foregoing may further take into account the association of PERCos processes and results with "external" cross-Edge computing arrangements for input, control, and/or other management purposes internally for PERCos and/or externally for any applicable portion of such external computing arrangement; and the like.
Appendix G is a non-limiting illustrative example overview of PERCos contextual purpose information/resource types.
PERCos processes resource use results in session consequences that are responsive, at least in part, to user purpose specifications, including purpose related user experiences and/or other results, such as, for example, information acquisition, modification, and/or storage; social networking interactions; user entertainment activities; and/or purpose related communications regarding computing and/or other device arrangement performing tasks and/or producing results, such as results from PERCos cross-Edge purpose influenced manufacturing process control, process and real world (e.g. traffic) flow management, scheduling, and the like. An inherent aspect of PERCos resource usage are sets of unfolding interactive processes driven in part by user input responsive to cross-Edge computer to user communicated information and ensuing user interface functions.
Some embodiments of PERCos systems incorporate purpose class applications and other Framework Constructs that assist users in progressively expressing and/or satisfying purpose related user understanding as it evolves during and/or across one or more sessions. This includes user purpose related understanding improvement, refinement, and/or alteration resulting from changes in user knowledge during the course of one or more such PERCos purposeful sessions. PERCos can enhance this knowledge/perception progression by providing user purpose-supporting results development environments that enable capabilities not found in traditional "search engines," "information retrieval" tools, and/or "knowledge management"
systems. Such traditional tools do not support the specifically evaluative and purpose-directed aspects of PERCos standardized contextual purpose expression environments. For example, PERCos users can employ such domain specific purpose related environments for Big Resource identification, evaluation, prioritization, management and utilization and/or purpose results development. These environments can both optimally relate to PERCos Big Resource organization and further provide specialized user/computer purpose related tools for navigation, knowledge enhancement, and exploration.
The nature of identifying productive resource tools for characterizing purpose satisfaction, and often the quality of user use of such tools, normally differs in correspondence to a user's relative command over the pertinent subject matter. This differing usefulness of tools, and manner of tool use, is due to a user's relative purpose class and/or category expertise level as well as the nature of the specific user purpose at a given point-in-time. PERCos levels described below generally correspond to decreasing user specific subject knowledge and/or clarity of purpose and/or decreasing comprehension regarding relevant candidate and/or actual tool usage considerations.
It seems self-evident that the less one knows about issues relevant to the area of interest central to a set of purpose processes, the less informed one is regarding relevant criteria for successfully furthering such processes. Generally, this view of user relevant knowledge levels and resource gathering/usage strategies can be simplified into the following three groupings which correspond generally to differing "levels" of information gathering considerations, from acquiring highly specific information items to knowledge discovery in unfamiliar Domains. These relative levels are:
1. With purpose level 1, users knowledgeably, with sufficient expertise, pursue purpose with such users retrieving, organizing, evaluating, and/or employing resources, and such users can reliably describe, locate, and/or interpret (e.g. evaluate contents) appropriate one or more resource sets. Such users, under such circumstances, generally understand the implications of, relative usage values related to, and usage control parameters germane to, relevant resource sets and their components. Normally these user abilities reflect the user's knowledge command over relevant Domain and/or sub-Domains and/or related categories.
This Domain related command enables users, for their respective objectives, to provide effective resource identities, e.g. resource names, web locations, explicit descriptive characteristics, and the like, to access, select, and/or use such desired one or more resources and further to interact with such resources with such reasonable proficiency as to result in "sufficient" purpose satisfaction. A simple example is a user searching in the Open Table reservations Cloud Service on the name Three Seasons restaurant in Palo Alto, CA to reserve a table at a specific time for a given night or a user entering Apple Computer, or USPTO, into a Google search box because they want to "go" to Apple's main website or to the U.S.
Patent Office homepage.

2. With purpose level 2, users wanting to learn about domain information set who have relative clarity regarding their desired purpose Outcomes, but less clarity regarding identifying and/or using optimal resources. Users identifying, evaluating, and/or provisioning such resource sets generally have "sufficient" awareness of their specific end-purpose objectives and related relevant one or more Domains and/or specific Domain portions and/or related categories to formulate CPEs and respond to resource opportunities in a generally informed manner. But with purpose Level 2, user information command and/or understanding of any such Domain and/or Domain portion and/or category is limited and there is an absence of explicit clarity regarding optimal resources and/or purpose processes. Such users normally desire a set of unfolding processes reflecting their knowledge accumulation/progression that leads to user purpose results/experiences and potentially to "sufficient"
purpose satisfaction, an Outcome set.
3. Purpose level 3 involves users exploring within one or more Domains and/or sub-Domains and/or other categories about which they have very limited and/or incomplete knowledge and where much of their learning has elements of a discovery process and where user purpose(s) is a developing, unfolding knowledge and/or experience set resulting from such learning progression.
These usage categories may overlap and further involve one or both of the following:
1. Purpose level 4 users objective includes experiencing as a purpose or purpose thread, where such experiencing, e.g. is listening to music, laughing at experiential input, enjoying a multi-user gaming session, participating in a chat session or teleconferencing get together, and where such experience, versus the acquisition of knowledge and/or the taking of some action, is a purpose objective set, 2. Purpose level 5 users objective includes sharing and/or other cooperative interaction, where the objective is a cooperative interchange between users, and where such cooperative interchange is a purpose objective set, such as collectively working on a document, exchanging communication, and/or undergoing a shared learning session.
PERCos can play a key role in enhancing purpose level 1 activities, for example, providing a resource set that enhances user understanding/sophistication related to a purpose set, and therefore revealing to a user the value in reframing purpose level 1 expressions to realize the enhanced value of a more knowledgeable/sophisticated perspective. But PERCos is particularly focused on purpose level 2 and/or 3, as well as any associated level 4 and/or 5 activities. In such cases, purpose is primarily about the identification, evaluation, prioritization, acquisition and/or provisioning of one or more resource sets best in alignment with users initiating, interim, and/or Outcome purposes. Generally speaking, PERCos isn't in most embodiments primarily about providing an "answer" to a retrieval request, such as search and retrieval products do. Rather, for example, PERCos is about resource related processes that provide a user set with best "fitting"
resources and/or resource capabilities/portions for realizing a desired Outcome. For example, the use of PERCos identified resources provides an environment, information, and/or the like that optimizes providing directly applicable "answers" responsive to user purpose sets, and/or provides process support leading to more relevant answers and/or other information, evaluations, queries, and/or the like. In the latter instance, PERCos is not providing a specific answer, but rather tools that a user employs to realize objectives through an unfolding process set, which may include answers and further learning, discovery, and/or requests.
In some embodiments, PERCos is an architecture for identifying, managing, and/or enhancing the benefits resulting from, purpose fulfilling resources. For example, PERCos may identify a resource set that may best serve user purpose, and further PERCos and/or a PERCos plug-in and/or API may provision capabilities within such a resource set that may provide a responsive environment tailored to developing and/or achieving a class of purpose of user desired Outcomes, and where, for example, the use of such resource application and/or other resource set of capabilities may provide an "answer" desired by a user set, in contrast to PERCos itself providing such an answer.
PERCos provides means to organize Big Resource, including Big Data, and provides further means to identify, evaluate, prioritize, provision, and/or use user desirable purpose fulfilling resource sets and/or capabilities.
Defining this new partnership between humans and their computing arrangements, the marriage of the differing context, circumstances and capabilities of differing people and computing resources, requires a new architecture for human-computer interaction that supports eliciting, interpreting, specifying, and/or otherwise identifying and/or initiating human purpose-satisfying Outcomes. Even for the less demanding simpler end of the usage spectrum where the user is better informed regarding the domain of their purposeful activities, this new broad architecture approach can provide significant benefits to many users.

Broadly speaking, with some embodiments, there are at least four major uses of PERCos systems:
1. Purpose-responsive Big Resource navigation, exploration, evaluation, retrieval, and/or provisioning.
2. Purpose-responsive organization and management of resources, including for example, information, applications, participants, local and cloud services, CPEs, frameworks, and foundations, 3. Provision of purposeful input into processes, applications, and/or automation sets (both new and legacy), such as word processors, presentation software, spreadsheets, conferencing (including teleconferencing) applications and services, recommender services, search engines, manufacturing and/or value chain automation systems, communication networks, messaging systems, and other productivity and workplace applications such as analysis, modeling, and decision making programs, and the like, the foregoing through, for example, data communication, application layers, or other modifications, including plug-ins, and 4. Invoking and/or developing specific purposeful activity set environments and/or other Constructs, including, for example, tool sets that may, take the form of purpose class applications that may be comprised, at least in part, of a variety of complementary resources that provide a user with a synergistic, purpose or purpose class specific, user intent fulfillment computing environment.
With some embodiments, each of these categories and/or any category combination and/or overlap and/or any purpose class and/or domain and/or class subset arrangement, including any associated member, may be supported by one or more special purpose "interface modes" that optimize and simplify user interactions for one or more purpose classes and/or CPE types. Such interface modes may suggest and/or implement maximization of resonance to improve effectiveness for purpose, and where such interface modes may optimize resonance through algorithmic strategies employed by Coherence processes, local to the user, in the network, and/or at cloud service locations, the foregoing in preparation for operating Purpose Statements, in similarity matching, in further filtering or evaluation and/or prioritization and/or other PERCos resource organization and/or user interface activities. The foregoing can be employed, for example, as users' purpose activities and PERCos processes unfold and evolve during and/or across sessions. Such interface modes may further employ intelligent user assistance by incorporating expert system tools, such as faceting engines, semantic information databases, and/or expert database capabilities, as well as, for example, other user selection and information visualization features.
Some embodiments may explicitly provide one or more purpose navigation interfaces and/or functionally similar means to minimize the effort for a user to visualize, understand, and/or reveal purpose relevant and/or otherwise interesting and/or useful aspects of, and/or otherwise control representations of, at least one or more portions of one or more major purpose-related Dimensions (or any portions thereof) and/or purpose related metadata. This includes user response in evaluation of and/or selection of resources and/or relevant identification and/or evaluation variables, including resource relationships and/or combinations, where the foregoing may be used to support the managing of resources for purpose satisfaction including, for example, user knowledge development. For example and without limitation, a purpose navigation may provide means to examine, control, and/or modify the "expression" and/or organization of a current interface mode, Master Dimensions, Facet, other Dimension information, purpose expressions, resource conditions/parameters, including, for example, conditions related to resource provisioning and/or use, user characteristics and preferences and/or other important contextual elements and/or sets not included or specified in a Dimension, and/or any portions and/or combinations of any of the foregoing.
PERCos, in some embodiments, treats all processable, published elements as resources in an unbiased, specification managed manner. This includes purpose fulfillment contributing elements that are represented by specifications with which PERCos may directly or indirectly interface and provide control contributing input. PERCos embodiments can provide specialized purpose fulfillment resource organization schemas employing, for example, purpose and resource class organizations with resources as class members, as well as in the form of related purpose ontology groupings, such as at least in part relational ontologies having resources associated with ontological positions, and purpose indexes that include, at least in part, purpose Dimension variables for efficient and easy parsing/filtering of vast resources stores into purpose responsive resource candidate sets.
In many embodiments, a key to PERCos performance is its unique organization/management of resource stores and its further, associated tools for interrogating such store arrangements, for example, PERCos tools that enable interrogation of Big Resource for similarity matching to user Contextual Purpose Expressions. In certain embodiments, resource publishers and/or creators and/or other Stakeholders declare descriptive CPEs and may further associate one or more other purpose related specifications, wherein such Stakeholder declared specifications may be descriptive of resource usage purpose information, including, for example, in the form of Core Purposes and purpose germane contextual information. Such Stakeholders may further declare any such resources as members of one or more purpose related classes, where such purpose classes and/or purpose class structures may have been declared by Domain experts for structuring purpose class resource neighborhoods to support relational approximation association with user purpose expressions associated with such classes.
Authorities, including experts and/or utilities and/or standards bodies, associations, and/or the like, may declare such purpose class arrangements for their respective one or more associated Domains (e.g., physics, astronomy, medicine/neurology, consumer electronics audio), to enable resource management and administration of resources. Such declarations may include associated CPEs and/or other purpose expression specifications declaring purpose associations for such purpose classes and, as a result, for their declared resources that function as their class members. Such purpose class arrangements, when for example declared/specified by one or more Domain experts, for example functioning as an effective domain class committee, may identify purpose classes that, in their judgment, correspond to conceptual neighborhoods so as to allow purpose supporting resources to be organized according to their pertinence to fulfilling user purpose concepts. This may prove useful where a user CPE is sufficiently similar to a purpose class CPE, or some subset thereof. In some embodiments, resources may be declared as members of a plurality of such classes, which may be associated with any logical taxonomic and/or ontological arrangements.
Certain, or any, third party Stakeholders may, in some embodiments, also declare CPEs or other purpose metadata specifications as associated with, or function as members in, any one or more resource sets, purpose classes, and/or resource portions/capabilities to enhance resource and/or purpose class member user purpose matching, including filtering, identification, evaluation, prioritization, provisioning, and/or use. This declaration of, for example, resource CPEs and purpose classes, by resource creators, providers, and/or other Stakeholders, provides, along with other PERCos capabilities, highly efficient scaffolding for bringing users, based on their purpose expressions and any associated input, into an appropriate resource "neighborhood," and provide a basis for users to proceed with fulfilling, in particular purpose level 2 and level 3 objectives, and which may further involve level 1, 4, and/or 5 objectives.
Many users prefer to deal with standardized and/or familiar interfaces and conceptual models, and don't want to learn a new interface or new model for each new purposeful interaction. Most users prefer simplicity over complexity and it's an important priority of PERCos to enable easy, efficient purpose expressions means. The vast range and variety of nuances of possible purposes and experiences can, in the absence of consistency, standardization, and expression bounding (filtering), exceed the complexity that most users are comfortable dealing with most of the time.
One standardizing and conceptually simplifying PERCos technology set is organizing contextual variable expression, and associated values, in simplified Dimensions and, where applicable, sub-Dimensions. Dimensions represent conceptually logical groupings of differing contextual perspectives and each Master Dimension has a limited number of standardized, easily interoperable and interpretable Facets. Dimensions in certain embodiments comprise a small set of conceptual familiar to user groupings, enabling users to easily "relate" to user purpose enhancing key Dimension characteristics. In one embodiment, PERCos supports five primary Dimensions, including Core Purposes, for example, and user, resource, Repute (assertions, et al.) and symbols.
Dimensions beyond Core Purpose may be used to great effect, for example, in Contextual Purpose Expressions as further specification of user purpose(s) beyond that initially specified by one or more Core Purposes. Dimensions have a wide and flexible applicability, and can help reduce user expression and navigation complexities by providing logical grouping values for similarity/matching, prioritization, and navigation and normally providing approximate contextual summary attributes that contribute to PERCos relational computing and help users relate and translate user classes and concepts to computing declared classes.
These features are widely applicable and can serve both to orient users within a PERCos cosmos and to assist them in retrieval, learning and edification, and navigation and exploration.
A Dimension is a PERCos expression structure representing an organizational subset of purpose expression contextual specification and approximation. In some embodiments, Dimensions may have standardized, interoperable expression Facets (e.g. subclasses of Master Dimensions) for efficiency, understandability, interpretability, and/or inter-operational consistency. Such Facet set and selectable options may be limited to a set that has been pre-defined for the embodiment by a Utility and/or other standards body set, and might in some embodiments be augmented, for example, by any that have been declared and published by experts or others independent of the standards body set, such as parties associated with an affinity group, such as a professional association.
In some embodiments, additional Dimensions, either Domain-specific or cross-Domain, may be declared by Domain set specific acknowledged experts, standards setting one or more bodies, and/or by Participants for their own use. However, unstandardized personal Dimensions may not be interoperable and those declared by a group may only interoperate within that group.
A declared context is a set of resource and/or system selected Dimensions Facets, any associated values, and any other, such as auxiliary Dimension information, specified as a component set for purpose expression, and constraining purpose Outcomes to reflect user objectives that in some embodiments complement Core Purpose Expressions and/or other broader CPEs, and may be employed as locally stored and/or as published building block components available for user and/or Stakeholder use.
In some embodiments, a relatively small number of Dimensions representing basic general forms of PERCos specification groupings will be distinguished as Master Dimensions, which are logical major groupings of characteristics that may significantly influence, for example, user resource identification, similarity assessment, prioritization and/or other organization, navigation, filtering, provisioning, and evaluation. These basic PERCos specification types can function as key simplification concepts for user purpose expression understanding and organization, facilitating user and Stakeholder input and comprising basic high level computer types of PERCos specification user and Stakeholder input. In some embodiments, PERCos enabled interfaces will provide easy access to, and control of, Master Dimensions as general specification and resource navigational tools. Master Dimensions, as a simplification organization of contextual attribute types, functions as a means for assisting user understanding and expression of contextual priorities and may help enable Coherence and/or other PERCos process sets to efficiently manage and functionalize the combination of various contextual dimensional input to be employed in similarity matching, purpose class assessment, resource provisioning, and the like. Given the standardization and interoperable features of such Dimension specifications, and in some circumstances, information derived at least in part from such specifications, Dimension information or such related information can be employed efficiently in approximation similarity matching to purpose class and/or other resource purpose specifications to simplify processes and constrain large resource sets. Some PERCos embodiments provide interfaces that provide easy access to, and control of, the balance among such Dimensions and their Facets and any values, as general navigational tools.
PERCos employs Quality to Purpose assertions of experts in the form of Repute elements employing standardized and structured assertion one or more facets, which may have associated values, and/or other standardized evaluation representations. Such evaluation representations represent the quality of a given resource, resource set, and/or resource class to satisfying a purpose, or contributing, along with other one or more resources to, a purpose, purpose class, resource, certain other PERCos Constructs, and/or one to or more associated resource quality of usefulness and/or reliability parameters. The foregoing may be standardized for interoperability, ease of use, and/or to represent an approximate class for a resource characteristic grouping employed as a filtering and/or evaluation vector.
Additionally, PERCos purpose fulfillment can employ other PERCos Constructs such as, for example, purpose class applications, purpose Frameworks, purpose user Foundations, purpose plug-ins, and/or the like, all the foregoing providing building blocks for creating purpose fulfillment environments and supporting complementary, efficient evaluation, management, and/or provisioning of resources in satisfaction of specific user purpose expressions specification one or more sets. Such PERCos Constructs, where applicable, are used in conjunction with direct user interface input, purpose/resource matching and similarity, and Coherence construction and management of operating Purpose Statement specifications, for resolving optimized resource identification, prioritization, provisioning, testing, and session monitoring and management.

A PERCos unified architecture of purpose specification and purpose responsive resource Constructs helps ensure, in a broad variety of cases, that human purposeful computing activities are optimally realized, both in quality and efficiency of outcome and subject to relevant contextual considerations. Such a unified cosmos of purpose specifications, declared by users and published by Stakeholders associated with resources, coupled with associated Reputes, Creds, FF, and EF filtering input, Constructs, and Coherence monitoring, analysis, and resolution and other PERCos local, cloud and network services, optimizes the identification, evaluation, and provisioning of resource sets to enhance user purpose fulfillment when user purpose focus extends beyond areas of user expertise and ability to reliably identify optimal resource sets.
Figure g illustrates an example overview of Foundation and Framework and other resource matching for cooperative alignment for purpose optimization.
The PERCos combination of purpose related specifications and Constructs, purpose and other class information stores, Coherence Services and other PERCos services, both local, network, and distributed, allows the full breadth of possible contributing resources to be integrated as a single environment supporting a purpose, experience, resource, Context operating system and/or services environment. This described matrix of complementary technology domains rationalizes the nearly boundless resources of the web into a practical, accessible, and responsive operating context and supports best general overall performance. In sum, the PERCos technology domains, through their complementary performance, enable identification and alignment of potentially best for purpose resources from diverse, vast distributed resources arrangements.
This cooperative coordination of differing specifications, technology operations, and process steps supports alignment of resources opportunities that are optimally focused on supporting purpose fulfillment processes with the best possible resources sets consistent with user context and purpose(s).

PERCos implementations may employ PERCos Coherence mechanisms to resolve incomplete and aggregated purpose related specifications and associated stored information into practical purpose optimized operating Purpose Statements. Coherence Services in some embodiments can manage the provisioning of operating specification process instructions through the interpretation, integration, completion, and/or conflict resolution of purpose processing input.
Coherence processes may take place at any one or combination of local, network, and/or cloud service locations, that may respectively contribute to resource evaluation, proffering, and/or provisioning, including pre resource combinatorial and/or contextual testing, and session processes including PERCos session process monitoring, testing, and/or collecting/storing session states, information, and/or process flows, the foregoing being at least in part performed based on session related rules and/or control algorithms (such as included in CPEs, Purpose Statements, profile information, resonances, Foundations, Frameworks, class applications, purpose class and other purpose plug-ins, and the like.).
PERCos in some embodiments, may support, for example, Participant, including Stakeholder simplification types, specifying testable and/or reliably certified Participant characteristics in user CPEs. Such types may be used in standardized and interoperable manner for contributing to the filtering of candidate resources, such as for identification of experts, social networking purposes, and/or the like. Such processes may, for example, provide a limiting, specific characteristic set for matching with Repute Creds, EFs Effective Facts, and/or FFs Faith Facts for finding corresponding appropriate asserters (and/or Cred Role performers) having the appropriate characteristics so as to help ensure optimum expert input in managing large resource sets into prioritized, constrained sets. Such characterization simplifications, as applied for similarity matching to Repute publisher, creator, and/or provider characteristics, can help constrain, for example, the set of all Creds expressing Quality to Purpose value sets regarding a resource set (or a portion set thereof) to one or more expert types who have appropriate relevance, for example, reputations and/or credentials, as demonstrated by Creds and EFs on them. This enables a user to employ for assertions and/or factual claims regarding a resource set, a filtering process on the characteristics of, for example, Cred asserters, that is parties with points-of-view, and only, for example, those asserters satisfying such user required characteristics who have made assertions regarding a best resource for a purpose or on a specific resource's quality might then be used as input towards identifying, evaluating, prioritizing, selecting, and/or provisioning a resource set.
Cred, EF, and FF characteristics may be in some embodiments associated with one or more of Reputes Creds, EFs, FFs, Stakeholder (such as, for example, publisher, provider, editor, and/or asserter, and/or the like), and/or the like. These characteristics are descriptive attributes, and may in some embodiments comprise, for example, an adaptable constrained available subset of such characteristics, where such available choices for user specification are limited to subset characteristic types that are logically related, for example of some particular value, to a given user Contextual Purpose Expression and/or associated purpose class. In order to identify Creds and EFs created, published, and/or provided by parties having sufficient desired qualities (and/or in some cases not having one or more certain specified qualities), user sets may select from a list of such categories proffered, for example, in response to user specified Core Purpose or the like, and where after a user set selects any one or more categories, such user set may then review, for example with a faceting interface, a list of options associated with each respective category, for example, where such options that are available were selected by, or otherwise identified through processing that produces a constrained list. Such a constrained list may have been provided as a result of some expert set and/or administering authority determining an optimum or otherwise logical set providing desirable user selectable characteristics, associated with a given Domain, purpose class, resource class, and the like. Such expert, consulting, authority and/or the like set might publish their set lists, at least a portion thereof being related to a specific current purpose expression, such as being associated with a purpose class, resource class, Domain category class and/or any other relevant taxonomically and/or ontologically related grouping.
For example, with a choice set in response to a user Core Purpose 'Learn' 'earthquake risk'," an expert set might provide as a recommended faceting option set for selecting experts with graduate degrees, experts who've published peer-review articles in the area of the Core Purpose, and experts with professorship positions in earth sciences or geology or the like from U.S.
national universities, or from "top" 10 universities, and/or from top 100 global universities and research institutes in the earth sciences domain, and/or from government scientists, and the like.
It may be significant in some embodiments in support of crowd and/or specified group discussions and user set learning, discovery, and experience processes, that not only resource items have unique identification, as PERCos Formal and Informal resources have as a consequence of their publishing and related registration processes and/or as are elsewise interpretable in a reliable manner by PERCos related processes and/or parties, and that subjects of such resources that are other resource instances have by extension (and therefore may have directly associated with them associated unique identity sets), but that non resource abstract concepts also have explicit identifications, where they allow declared classes, members, and/or other subject instances to be individually organized and identified in ontologies and taxonomies.
Such at least in part abstract subject matters may, in some embodiments, be at least in part published as resource instances and/or instance sets by general and/or Domain Experts and/or authorities so as to provide one or more taxonomy and/or ontology arrangements, such as groupings, for subject and/or subject approximation class/neighborhood consistency, the foregoing being employed and providing for, at least in part, subject associated identity services.
Such pre-setting of subject, for example, popular, timely, and/or important such subject approximations, may facilitate, in some embodiments, user ease of use and might employ, for example, faceting interfaces or the like in a manner as discussed elsewhere herein for selection of approximation/neighborhood included items such as class member instances.
Further or instead, such PERCos expert, utility and/or other standards setting set arrangement(s), may, in some PERCos embodiments, support Domain specific and/or universal, that is PERCos cosmos wide, naming and identification structures that support both resources types, that is explicitly published items, and abstractions, such as concepts, labels, and/or the like. At least in part abstractions/generalizations naming and identification structures, such as one or more taxonomies and/or ontologies, can provide an at least in part, prepared scaffolding for the issuance of specific subject IDs, such as upon request of a user or Stakeholder, or as may be automatically requested by a PERCos service as a result of some evaluation and/or aggregating process. An integrated PERCos universal and/or Domain set taxonomy and ontology arrangement can provide the means for the automated issuance of unique IDs, for example, (a) in response to parsing of such subject abstract concept specifications, by identifying Core Purposes and/or Domain categories and/or associated declared classes and/or the like and placing a user or Stakeholder and/or other party submitted subject concept description into one or more appropriate taxonomical nodes and/or ontological "positions" along with issuing a specific or approximation/generalization corresponding group, such as a resource class, identity, and/or (b) employ at least in part a standards body (association, corporations, other organization, and/or other like group) agent arrangement for human agent inspection and at least in part determination, with the aid of such ontological and/or taxonomical tools, of appropriate classification positioning and associated unique or group identity set, for example, and/or the like. For example, classification may, in some embodiments, in addition or alternatively assign a concept representative identity to a submitted concept, whereby an identity represents a plurality of differing but closely related concepts in a concept approximation structure established, for example in some embodiments, to support consistent and/or aggregated and/or co-provisioning of such approximations while, for example, allowing certain flexibility in specifications for practical user approximation and resource management purposes.
In some PERCos embodiments, subject concept specification may employ (for example in resource information arrangements and in CPE specification arrangements) certain PERCos Master Dimension interface technology types, such as standardized logical grouping specification Facets, which may employ verb, category, adjective, adverb, preposition and/or the like where specifications options may constrain to logically appropriate and/or likely choice sets as a user or Stakeholder specification process unfolds, for example, when progressively selecting a category, a subcategory, an adjective, a verb, and/or the like in any logical order.

Concepts representing abstract, generalizing notions that approximately frame a Domain area can also be published individually or in some logical grouping as resources, wherein the subject of the resource is an abstract, generalized subject, e.g. Wild Salmon, Ceramic-on-Ceramic hip prostheses, global warming, Wahhabi Islam, Greek Orthodox Church, and/or the like. Such resources could then include or otherwise have associated purpose expressions that may correspond to prescriptive CPEs of users. This would enable users to identify, in a purpose oriented, contextual manner, standardized subject matters and if stored with the subject matters, their identities, including such abstract concepts. For example in some embodiments, if a user wanted to locate resources for asserting on, or reviewing Creds on, global warming, they could create a CPE 'Assertion' 'Global Warming' and through processes discussed herein, identify purpose class and/or domain category set (e.g. a domain category called "Global Warming"
whose member resources (and/or resource portions) could be prioritized by similarity matching and which, at least materially in part had members that may correspond to user purpose expressions and which are identified through inspection of such resources information sets. This could be, for example, be followed by a second step PERCos process of examining such members, for example, review Creds by Ph.D. scientists in Environmental Sciences (and/or the like) regarding global warming which express in the aggregate, for example, a Reliability Facet value of above 7 on a scale of 1 to 10 (or, for example, a 3 on a scale of -10 to +20). In some instances the Cred resource might include other information associated with included subject matter instance or instances or groups and/or Facet assertion values, where such other information complements the information set in the subject of such member resource set. Such complementing information may include for example, in some embodiments, numbers of reported use of a resource instance, or the resource's subject matter or group, Creds on a subject matter or group (such as which subject matter instance might be recommended using various Cred (and/or EF and/or FF) techniques discussed herein as the most useful to user purpose, that is most popular and/or most used by participants with certain characteristics, and/or the like.
Further information might be provided or referenced by such resource where such information is a complementary information set, such as, for example, an information set from another party that complements and/or supports at least a portion of the assertion set of a Cred or in some manner supports and/or complements and/or provides counterpoint information (e.g. as provided by aggregate Cred sets) contrary to resource subject matter.
Cred subject matters may be uniquely identified through user and/or Stakeholder explicit referencing of one or more, for example, recognized, at least in part, topic matter directories, databases, reference materials, and/or the like subject matter provided by one or more authorities, such as web services. Such authorities, such as Wikipedia, have unique identities, e.g. web page addresses to specific topics, which can be automatically interpreted or extracted through the use of a PERCos compatible interface. But while there are some ontology services that can provide an identity at least in some domains, today there is no service that assists, that is assigns and administers a member cosmos of unique identities to user subject instances, so as to support such resources, and their subject identities, in a global, systematic, intraoperative resource cosmos. Such service could, for example, also provide various characteristic descriptors associated with a taxonomic and/or ontological group to which such subject is assigned, such as leading purpose expression classes, CPEs and/or other purpose expressions, Creds and/or information derived from them and/or the like, and/or other items with relationships to such group and/or group member sets.
Some PERCos embodiments may provide identifier standards of expression to enable such interoperability interfacing. In some embodiments, such advantageous capabilities support Cred assertions regarding topics that are, at least to some degree abstract, (e.g.
Wild Salmon, Fast Cars, Stone Wool Insulation, Portable Music Player) versus a subject that represents an explicit real world resource having an operatively unique identity, and for example, associated unique name (e.g. Hilary Clinton, Republican Party, Ford, Safeway, Sony Corporation, Oxford Shorter Dictionary, Merriam-Webster' s Unabridged Dictionary for iOS 3.29). Such standardization can be provided by one or more PERCos environment resource Domain or general coverage subject descriptor utility, standards body, and/or other provider set, such as a for profit corporation cloud service. The foregoing can enable consistent description of non-resource subject matters by assigning explicit identities to, for example, topical abstractions in a form interpretable, and in some embodiments, provided by, a root standardization authority/standards body for a PERCos embodiment, by Domain specific such bodies, and/or for other environments. This standardization and web based services (and/or local or network based information stores) can support subject matter disambiguation by offering specific subject matter instance suggestions, and their associated unambiguous identity (e.g. an explicit alpha and/or numeric code) in response to an apparently ambiguous subject matter specification, for example by employing semantic analysis and/or look-ups to suggested synonyms, alternatives, and/or the like, and/or by supporting user interface expert interfaces, such as faceting interfaces, providing users with logical choices to select from for disambiguation, which may then be followed by assignment to an existing identity or the issuance of a new, operatively unique identity.
Abstract Creds, in some embodiments, can employ an abstract Cred Master Dimension, for specifying simplification and approximation and Cred information management purposes. For example, an abstract Cred can be associated with a purpose expression where a Quality to Purpose may be expressed regarding the value of an abstraction in serving user purpose fulfillment. For example, an Abstract Cred may have a subject "Wild Salmon,"
or "Wild Alaskan Sockeye Salmon." A Cred publisher can specify for a Cred an abstract purpose "Good Health" or "Good for Living Healthy" or the like. The Cred publisher can in some embodiments, for example, associate such a purpose expression with one of the described salmon subjects and provide a value 8 out of 10 on a Quality to Purpose (e.g.
Good for Living Healthy) scale of 1 to 10. In certain embodiments, abstract (and/or other) Creds may employ a Core Focus set as an alternative to, or in combination with, a Core Purpose set, so, for example, a Core Focus might be expressed as "Good Health" where in any embodiment considered sufficient, and where a purpose verb or the functional equivalent, for example, may be logically assumed, where, for example, the Core Focus may be comprised of an adjective and noun pairing. User interface modes described herein for faceting for Core Purpose and Facet specification and where logical, constrained set options are provided through user interface selection may be used in a corresponding manner with Core Focus arrangements, such as offering logical adjective choice list for initially selected category as may have been determined by experts with a standards organization, such as associating "good" or "bad"
or "delicate"
adjectives with "health", but not offering "red" or "loud" or "tasty" as adjectives with "health."
With PERCos technology, user and Stakeholder computer interaction can involve, for example, in some embodiments, users and Stakeholders at least in part providing standardized purpose characterizing input in combination with one or more of: associated sets of other purpose relevant Specifications; purpose related specification Coherence resolution, including, for example, some set of specification inspection, identification, evaluation, conflict resolution, completion, multi-resource amalgamation assessment (for example including user purpose related provisioning assessment), and/or the like; provisioning of resources for PERCos session set at least in part associated with such processes and specifications;
associated initiating and unfolding of user experiences and/or other Outcomes, including, for example, support for at least in part recursive or otherwise unfolding user evolving processes leading to purpose Outcomes and/or interim results.
The foregoing can contribute, for example, to a user/computing arrangement purpose fulfillment operations set with purpose results generated using purposefully selected and/or assembled resources. This may involve in some embodiments, PERCos users and/or computing arrangement sets using resources that have not been published as a PERCos resource, but which may be provisioned by PERCos to satisfy specific purpose related specification(s), such as using a well-known word processor in a certain manner, for example performing word processing functions as a component within a PERCos Framework. In some embodiments, such a resource instance, for example, Microsoft Word, might not have been published as PERCos resource, but, for example, one or more Stakeholders, an authority, expert, user, Repute publisher, and/or the like set may have declared that Microsoft Word is an acceptable resource, desirable to use in fulfilling word processing Roles. For example, Word may be provisioned within a Framework identified by a user and/or PERCos computing arrangement set as a Framework of choice and having a component function (which may include interface interactions and locations) Role for word processing that may contribute to certain purpose fulfillment related activities. In such instance, for example, Repute, and/or other services may declare a traditionally published resource as a PERCos Informal resource, or such may be inferred as a result of such a Repute assertion set. For example, a recognized expert or expert group may identify and publish an "Informal" resource having a CPE set associated with a subject set comprising at least in part Microsoft Word, and which is associated with sufficiently reliable resource subject identity information, and where such expert Stakeholder can be specified as the "informal"
publisher/creator of such a new PERCos informal resource, which resource may, for example, have associated with it (e.g. provided by such recognized expert set and/or organization) such other information as creator, original publisher, and/or provider resource (e.g. word processor related) information, including names, rights and/or one or more sets specifying other information regarding such resource, as may be necessary for use of such word processor.
PERCos resources may be provided in some embodiments, for example, in several different forms, for example: Formal resources, Implied resources, Ephemeral resources, and Compound resources (multiple of these forms may apply to a given resource instance and/or resource class, either as to one or more parts and/or as to the whole):
= A Formal resource is, at minimum, comprised of (a) a persistent, operatively unique identity (e.g. should not be ephemeral or intentionally temporary and unreliable as an identity, along with any enforcement of this criteria depending upon the embodiment), (b) a subject matter that is the processing and/or processable material (including, for example, a human Participant descriptive information, and which may, for example, include how to initiate contact, or use, of the Participant, for example, as a resource), (c) a formal publisher set (named, or otherwise identified as may satisfy a rule set, including having a persistent, operatively unique, identity, for example, as above) for such resource, and (d) at least one associated and context providing purpose expression such as a CPE, except in embodiments employing at least in part Core Focus instead of a purpose expression set. Such resources are interpretable by at least one or more PERCos embodiments, and their subject matter may or may not be useable, depending on the presence or absence of necessary other resources and/or conditions.
SuchFormal resources may contain or otherwise reference other descriptive metadata, such as author, provider, language, interface, user and/or other participant set usage history (for example generally and/or as associated to one or more purpose expression, participant, association with other resources/resources, sets), and/or any Repute information as described as a capability of a PERCos embodiment, or, for example of publisher, creator, provider and/or the like sets, for example, including associated use of EF and/or Ft sets. See figure a, a sample embodiment (that is, non-limiting) of PERCos Formal resource element information types. Formal resources are published, including registered, through use of an identity schema arrangement supporting plural, independent parties as publishers, wherein such schema arrangement provides information constituting and/or is otherwise employed as at least a portion of a persistent, operatively unique identity for such resource. Such registration schema may be at least in part managed, hosted, and/or otherwise controlled by, one or more cloud services and/or standards organizations. Such one or more services and/or organizations may accept at least a portion of such identity information or input thereon from such resource publisher set and/or another party set(s), wherein such information may supplement, complement, and/or otherwise contribute to such identity information. See Appendix A, a sample embodiment of a Formal resource element information type arrangement.
= An Informal resource is, at minimum, comprised of (a) a persistent, operatively unique, identity (e.g. should not be ephemeral or intentionally temporary and unreliable as an identity), (b) a subject matter that is the processing and/or processable substance of the resource (including, for example, a Word Processor such as Microsoft Word, that can be employed in creating and editing documents), (c) an implied resource publisher -- this may be an interpreted or otherwise inferred originating publisher of such resource, or this may be, for example, a different Stakeholder type such as a Participant provided and caused to be stored preference information indicating choice of Microsoft Word as word processor, or when a Repute Cred asserter -- or if sufficient information exists --a Repute EF declarer stipulates that Microsoft Word is a word processor, or when a user stipulates, or a user PERCos Foundation has been employing, a local version of Microsoft Word as a word processor, and (d) at least one purpose expression associated with such subject matter as specified by such implied resource publisher either directly by such publisher, and/or indirectly by a resource Creator and/or other Stakeholder set. Such informal resources may contain or otherwise reference other descriptive metadata, such as author, provider, language, interface, user and/or other participant set usage history (for example generally and/or as associated to one or more purpose expressions, Participants, association with other resources sets), and/or any Repute information as described as a capability of a PERCos embodiment, or, for example of publisher, creator, provider and/or the like sets, for example, including associated use of EF and/or FF sets. Informal resources are published, including registered, through use of an identity schema arrangement supporting plural, independent parties as publishers, wherein such schema arrangement provides information constituting and/or is otherwise employed as at least a portion of a persistent, operatively unique identity for such resource. Such registration schema may be at least in part managed, hosted, and/or otherwise controlled by, one or more cloud services and/or standards organizations. Such one or more services and/or organizations may accept at least a portion of such identity information or input thereon from such resource publisher set and/or another party set(s), wherein such information may supplement, complement, and/or otherwise contribute to such identity information.
= An Ephemeral resource can be, at minimum, comprised of a non-persistent subject matter that is a separately identifiable processing and/or processable substance arrangement that is dynamically produced, provisioned, and then no longer maintained, or not maintained beyond a short, session operatively appropriate time frame. An Ephemeral resource may represent a user who has not been registered or otherwise identified as a Participant.
= Compound resources have all the characteristics of Formal and/or Informal resources, but are further comprised of a plurality of Formal and/or Informal resources. Compound resources may also, respectively, be Formal, if all compounding resources are Formal, or Informal, if not all compounding resources are Formal.
Figure a illustrates a sample embodiment of a PERCos Formal resource and resource element types.
PERCos embodiments are particularly adapted to support user identification, evaluation, and provisioning of web and intranet located resources where PERCos treats such resources as population instances of a resource cosmos organized to support optimized "one-to-boundless"
purpose fulfillment computing. PERCos is, in part, a technology set uniquely supporting user use of contextually best suitable resources located anywhere, made available by anyone, and individually or in combination, and as may be best responsive to user purpose objectives. As such, PERCos embodiments distinctively support both conventional and uniquely enhanced user relationships with computing resources in support of user computing objectives. With PERCos, user relationships with computing resources can be at least in part be realized through user computing objective specification using a PERCos schema that is specifically designed to describe significant user intent generalizations through direct specification and/or inference of one or more verb generalizations combined with directly specified and/or inferred category denotations. These specification compositions, PERCos Core Purposes (when inferences are settled), may be used with a further contextual framing set, and may describe user objectives that reflect, for example, one or more of the following broad user intent categories:
1 Retrieve ¨ Traditionally, users search and retrieve through the use of succinct expressions employing terms that may be matched to indexes and/or other information organizations, that is, searching for terms and associated web pages having a "sufficient"
correspondence to such expression term sets. Such retrieval techniques are being used, for example, by Google/Bing for their search and retrieval services, which, at times may be enhanced by directory arrangements, knowledge graph visualization, semantic analysis, and/or other tools. PERCos can extend such traditional technologies by, for example, providing Core Purpose and/or other PERCos Dimension standardized and auxiliary and/or other embodiment contextual simplification specification capabilities that may substantially enhance and/or extend explicit search term operations through the use of PERCos Purpose Approximation Computing (PAC). PAC can improve conventional retrieval learning and discovery with, for example, enhanced information sets regarding resources and/or portions thereof by providing perspective/knowledge enhancing knowledge/information/experience purpose related neighborhoods and/or neighborhood information and/or by providing Coherence specification resolution services and/or Repute identification/evaluation/prioritization services, which foregoing may be enhanced or otherwise facilitated by relevant associated purpose class application tools and interfaces and/or the like.
2 Learn/Seek ¨ users are partially able to express purposes, that is users can frame general objectives, but do not have sufficient domain expertise and/or purpose specific knowledge to sufficiently specify retrieval requests for user known and desired specific one or more resource items and/or related processes, but rather users wish to initiate one or more learning process sets with the objective of improving user understanding regarding one or more specific information and/or experience issue sets.
3 Explore/Discover - users wish to obtain knowledge resulting from one or more process sets that include investigating information issue sets so as to identify one or more such information sets as user developing or developed focus, including identifying and employing investigation enhancing resource sets for acquiring information related to such initial and/or evolving issue sets.
4 Experience for users - users seek experiences for themselves, for example entertainment, games, movies, music, and/or the like.
5 Social and/or collective experience - users seek social experience that substantially involves interactions with other users, including shared, collaborative, and/or similar participation.
6 Tangible/Instantiate ¨ users seek outcomes involving commercial and/or physical world processes such as transaction results, value chain process management, manufacturing automation and output, digital package transmitting, and/or the like.
PERCos embodiments can uniquely support the CPE framing of user resource utilization objectives and related purpose Outcomes through its standardized implementations of user purpose expression capabilities. For example, in some embodiments, PERCos can support one or more standardized parameterizations of Core Purpose intent and other contextually appropriate criteria enabling consistent and efficient interoperable user and Stakeholder purpose characterizations. Such CPE framing optimizes user purpose fulfillment processes by, for example, enabling both generalized contextual user and Stakeholder purpose approximations and associated matching, and supporting Outcome sets as derived at least in part from purposeful utilization of optimum resource sets specifically responsive to such framing. Such resource utilization is a consequence of user and PERCos system and/or application expression and selection processes identifying, evaluating, prioritizing, selecting, combining, and/or provisioning one or more resource sets. In some embodiments, such sets are evaluated at least substantially in part regarding their responsiveness to user specification of standardized Core Purpose and/or broader Contextual Purpose Expressions associated with user and/or user computing arrangement related contextual variables, including in some embodiments, for example, standardized contextual Master Dimension Facets and any associated values, auxiliary Dimension information, user profiles, preferences, historical crowd behavior, and/or the like.

PERCos can identify resource store information elements that correspond to CPE
and/or related purpose formulation elements for matching and similarity determination processes that may, for example, evaluate and/or identify and/or select and/or prioritize and/or provision candidate resources at least in part as a result of calculating the correspondence and/or other relevance of candidate resource sets available through such information store(s) to user related purpose expressions such as CPEs and Purpose Statements, as may be supplemented by other purpose related information. A PERCos based system may also employ inference determinations in support of the specification of, and/or related to the processing of, CPEs and/or Purpose Statements and/or other purpose expression formulations such as expression verb constraining or identifying categories and/or the like, for use in resource selection, and/or resource utilization evaluation, and/or other PERCos operations, the foregoing in support of user purpose calculations to identify, evaluate, select, prioritize, combine, provision, and/or use resources for initiating, interim, and/or Outcome purpose fulfillment.
A Resource Cosmos for Purpose Fulfillment, Including Associated Learning, Discovery, Cooperation, Experience Support, and Outcome Automation A PERCos arrangement of resources and users may unfold over time and in part, in conjunction with PERCos standardization arrangements such as purpose expressions and their associated Master Dimensions and purpose classes, self-organize as a systematized purpose constituted resource cosmos. In some embodiments, this cosmos evolves primarily through the efforts of Stakeholders as they declare descriptive Contextual Purpose Expressions for respective resources, including for example, for Reputes assessing one or more other of such resource sets or elements thereof, and for which they may then, in some embodiments, declare one or more resource sets as members respectively of one or more purpose classes and/or other purpose neighborhoods. This purpose cosmos may employ such purpose expression, purpose membership, and/or Repute declarations associated with resources with, for example, user and/or crowd metadata such as, for example, related usage derived information associated with specific one or more purpose expressions, purpose classes, user classes, and/or the like. The result is an evolving cosmos of purpose related knowledge, experience, assessment, and actualization resources, known in PERCos as Big Resource. With PERCos, one or more "general" common purpose effectuating cosmos may be built substantially upon tools and standards for interoperable Contextual Purpose Expressions, purpose related Repute resource assessment, purpose Coherence resolving and optimizing including, for example, resource evaluation, combination, and/or prioritization, and supporting human/computer edge purpose fulfillment interface technologies and processes (such as Foundations and Frameworks). Some embodiments of the foregoing may, for example, support purpose class resource organization, Repute resource appraisal, and resource provisioning Constructs such as purpose class applications and other Frameworks, user computing arrangement Foundations, and purpose facilitation resonances. Implementations of PERCos interfaces and applications may support adaptations for both discrete purpose fulfillment Outcomes and dynamic experience continuums, the latter involving unfolding user/computer/resource arrangements and associated cross Edge interactions such as iterative user purpose expressions through specification and/or resource selection and/or resource portion usage, where the foregoing may be specifically supported by related interface purpose support processes such as purpose expression element faceting interfaces. Such user cross Edge PERCos activities may include multi-user common purpose sessions and over time multi-user purpose collaboration, for example involving multi-user collaborative document creation, cooperative web surfing, and shared entertainment experience (music, movies, game playing, and/or the like).
A principal aspect of PERCos purpose architecture is a "partnership" or otherwise cooperative and/or collaborative process occurring between users and machines, users and other users, and users and Stakeholders, whereby one or more humans at least in part guide machine operations towards satisfying their individual or shared purposes, initially and/or in an evolving process set involving the maturation of, for example, human perspective, knowledge, orientation, experience continuum, and/or priorities and/or the like. Through this interactive partnership, at least some embodiments of PERCos user/computer arrangement(s) can employ local and/or remote PERCos services and other resources that serve as portals to human knowledge, expertise, experience opportunities, and process opportunity, management, and Outcome control. Such embodiments can provide, for example, process management and other capability support of PERCos user/computer arrangement purpose Outcomes through, in part, the association of purpose expressions with respective resources, and, for example, through event management, including, for example, consequences resulting at least in part from purpose related programmatic instructions. As such, a primary role for general PERCos embodiments is the support of, including, for example, seeking to actualize, purposeful results, whether personal, interpersonal, commercial, and/or the like, and such support may, in some embodiments, include the gamut of user computing purpose objectives, from experiencing entertainment to social networking to user and/or group productivity to information learning and/or discovery to realizing commercial transaction fulfillment and/or or business process automation and/or the like and including any logical combination of the foregoing.
At any given time, users have certain objectives/desires whether explicitly understood or involving an evolving user perspective. To one extent or another, users undergo experience reflecting informational, experiential, tangible, and/or emotional/spiritual factors. To satisfy human purposes, PERCos transforms human perception of purpose into purpose expressions that orient PERCos computing resources to "best" attempt at supporting user purpose fulfillment computing processes. PERCos capabilities can extend into a computer context user purpose fulfillment perceptions by identifying, evaluating, selecting, combining, prioritizing, and/or provisioning resources and/or resource portions as purpose fulfillment tools and/or environments in response to user CPEs such as prescriptive Contextual Purpose Expression instructions, which may unfold as a result of a sequence of purpose related user/computing arrangement interactions, and which may reflect enhanced user knowledge, understanding, and/or experience satisfaction and/or other experience development. As a result, PERCos can supplant today's task oriented and silo computing arrangements with purpose specific support arrangements that may be influenced by expertise and framed for learning/discovering and/or other experience and/or results producing Outcomes. PERCos may specifically focus on satisfying "active" user purposes (or scheduled, time based, and/or event wise triggered and/or specified purpose specifications) by identifying one or more resource sets, including resource frameworks such as purpose class applications, that users can employ to provide satisfying and practically optimized purpose fulfillment results, and/or otherwise contribute to apparent to user set progress towards such fulfillment through unfolding PERCos and/or associated purpose application assisted processes.
The challenges of users relating to the inchoate masses of web (or other) resources stores, and the demands underlying properly exploiting available resources for learning, discovery, and/or setting the stage for "most" satisfying experience unfolding, provide basic catalyzing underpinnings for the PERCos purpose centric architecture. However well or poorly understood by its human actors, human activity at any given point in time has at its core a Purpose set.
Modem humans in the developed world -- in very sharp contrast to their ancestors -- may invest their time in many varied ways. Most people in the developed world are no longer shackled to the pursuit of food, whether in endless dawn to dusk agricultural, shepherding, and/or hunting tasks, as well as providing shelter and protecting one's group from predators and other humans.
With the advent of advancing technology and increasing knowledge, and in part due to division of labor and emergence of elaborate and often quite abstract activity types, human time, both commercial and leisure may now, in sharp contrast to even recent human history, be devoted to any of a vast set of activity types and content. These activity types can be placed into three categories, and these three categories often overlap, depending on the activity purpose and context. These three activity categories are:
1. Experiencing things, 2. Making things happen in the real world (e.g. growing food, building and maintaining shelter, earning money, producing goods, and/or the like, that is generally striving for productivity), and 3. Learning things which may inform each of the above, which is itself a form of experiencing.
What we may need or want to learn at any given time is a result of both the purpose we may be consciously or unconsciously be pursuing, given the context in which such pursuit is unfolding.
This context includes how much we know and may further include how much we know about how much we know. In order to improve on the results of our activities, to better our condition and improve the quality of our experiences, it would serve users well to be in the best reasonable position to know what others know as and when it would be useful, and further to be able to apply such knowledge in an optimally productive manner.
The advent of the connected digital world has brought about a quantum leap in diversity of human activity resources and associated pursuit types, focus, and context.
While generally, the human community has some sense of the enormous possibilities of being connected to such a seemingly boundless miscellany, no current technology set intelligently associates resource possibilities to one's explicit, current purpose. While knowledge graphs, other clustering, and/or the like can provide some guidance when generally exploring a domain, they are roughly drawn generalizing mediums largely structured according to the characteristics of things rather than the purpose of potential resource users. Generally such technologies fail to provide means that organize resources according to user purpose and, as a consequence, these technologies are unable to responsively identify and/or provision resources in a manner responsive to such user purposes. Further, since such current technologies are normally blind to user purpose, at least in any formal sense, they can't support capabilities that provide the assessment of resources regarding their quality in contributing to optimally satisfying a user specific purpose set, such as those provided by PERCos Repute technologies.

In some embodiments of PERCos, learning, discovery, and/or experience ("LDE") may be deeply embedded into cloud services, such as, for example, PERCos LDE
supporting capabilities related to PERCos Social, Knowledge, Commercial Networking Services ("PSKCNS(s)"). These PERCos capabilities provide innovative features that may transform the character of traditional social, knowledge, and commercial networking. With PERCos, by supporting users viewing other Participants as resources and potential common purpose users and by employing participant related specifications in user CPE
specifications, and further by universally viewing other direct, specifiable elements that may contribute to a PERCos session as candidate resources, users can learn about and/or discover, that is identify, evaluate, and employ a "best" set of other participants in PSKCNS context, and more broadly, an optimized set of resources for any given purpose.
Many modern computer users now share an awareness of the presence of a seemingly boundless array of resources that might seem useful generally, particularly for certain well known tasks ¨
Yelp may be useful in gathering information concerning crowd member reactions to, and aggregate ratings of, services such as neighborhood restaurants; similarly Amazon reviews can be useful in assessing reactions to products; and Netflix can inform regarding the crowd reactions to video entertainment; while IMDb is useful in obtaining expert movie reviewers views and scores for specific films and television shows; Healthgrades and Vitals in assessing hospitals and doctors; and eHow, Answers.com, WebMD, and Wikipedia, can responsively supply limited information responses on certain things. One major concern regarding these systems is that these services are not generally adaptive; they normally provide static characterizations of things (including services) with generally a highly specific focus on a preset category item. While these systems can provide useful information regarding certain limited categories of things, unlike PERCos mechanisms, they don't provide any significant ability to identify, or adjust, combine, and/or evaluate a resource to be responsive to a user's current specific purpose.

There are one or more services, for example 43 things (www.43things.com), which provide simple mechanisms for sharing what its users characterize as goals, but such a system does not provide means to significantly systematize and/or evaluate purpose, but rather allows anyone to chat about anyone else's natural language expressed goal and has means to generally associate different goal expressions to support some grouping. This often leads to a cacophony of comments, which may motivate some people regarding a goal because it seems shared with others, but is not about any formalized system for resource management, identification, evaluation, prioritization, selection, composition, provisioning, and/or usage support in a manner responsive to user purpose, that is to enable common purpose computing, including sharing and/or the like. For the above services, when a computing arrangement user ventures beyond the assertions of the crowd, and/or in more limited circumstances the assertions of experts for branded products, services, and entertainment, that is when one wishes to launch a learning process leading towards an Outcome about an issue whose specific nature is defined by a user's purpose and not a category ¨ the foregoing given one's individual constraints, interests, priorities, and/or state of knowledge and/or the like -- current technologies are not oriented towards providing the facilitating layer(s) that bring one to "best" candidate one or more resource sets such as facilitating an Outcome related to, for example, a technology, a perspective on certain scientific research, a manufacturing technique, how to fix something specific, a social or commercial networking objective, and/or the like.
Current social networking, for example through services such as Facebook, Google+, Twitter, MySpace, Instagram, and/or the like, primarily involve interacting with parties a user knows, may know, or has "friends" or other acquaintances in common. Those social networking services may also involve identifying or establishing threads or groups that share some stipulated interest, and one such service, 43 Things, is substantially focused on shared interest around a user natural language declared topic. But these networks are not general resource identification environments and are not structured as interface environments to, for example, Big Data and Big Resource. Generally, they do not provide a standardized contextual structure for purpose expression but rather support streams of comments from members associated with topics, where such comments generally speaking provide a smattering of disparate remarks and not a contextual purpose responsive resource array. These services are not designed around the principal of optimized user purpose satisfaction through identifying and provisioning desirable resources to support unfolding purpose satisfaction processes.
In certain PERCos embodiments, purpose class applications are particularly useful in supporting learning, discovery, and experience enhancement. In an emerging purpose based computing cosmos, people anywhere, of any inclination and ability and knowledge level, can, with some PERCos embodiments, publish resources such as purpose class applications, which are meant to support the learning, discovery, experience, and/or Outcome objectives associated with such applications associated CPEs. Such applications can function as specific purpose class (such as CPE) specific fulfillment environments and may be specified to support such purpose expression sets as narrowly and/or as broadly as may be specified by their design decisions and their concepts associated with such relevant CPEs. Such applications may incorporate any number and variety of purpose fulfillment subclasses, which may be formally declared as subclasses of such purpose class applications.
Over time and given sufficient participation, as well as sufficient evolution of Repute resources as filtering and prioritizing input, in some PERCos embodiments, users should be able to connect to a PERCos cosmos arrangement and be in the neighborhood of the best available resources and/or resource portions. Best purpose class applications may, for example, provide Domain specific guidance through interface and application capabilities that in a Domain specific manner support further learning, discovery, and/or experiencing options and processes that have been tailored by the talent and skill of such application publishers and/or their associated experts and/or based on user input such that learning, discovery, and/or unfolding experiences have been formulated by those having specific domain expertise, experience, and/or sufficient associated talent. Certain of such purpose class applications may be considered to be, according to Repute resources responsive to user specification, the "best of breed" given user concerns and other contextual conditions (for example, Quality to Purpose, Quality to Value, user budget, user sophistication, available time, availability/affordability of Role contributing application sub-resources, and/or the like).
In some embodiments, PERCos purpose class applications, as learning, discovery, and/or experience unfolding environments, can be oriented towards any set of purpose fulfillment processes and activities, from narrow to broad. These may involve relatively uniform types of activity sets to compound activity sets and such architectures may involve senior and more subordinate purpose class foci, as well as provide purpose, for example, class-oriented, user navigation tools. For example, a purpose class application might be created for the moderately knowledgeable in the Domain of Physics, this application taking the form of a knowledge pursuit/imparting environment comprised of both more general tools and more specific tools, such as an expert system interface arrangement guiding users through their respective interest focuses, such as learning about specific issues involving the intersect of molecular and nuclear physics information.
For example, in some embodiments, a user might specify a CPE as:
"Learn+Physics+Nuclear&Molecular+ModerateExpertise+<$200.00+PurposeClassApp"
("+"
adding an element and "&" being a horizontal connecting operator and "<"
standing for less than), which might be purpose identified and in part prioritized by an aggregate of Repute representation of Repute Creds published by Ph.D.s in Physics. Alternatively and/or in addition (by, for example, weighting variation, that is, for example, providing more weighting for) tenured Physics professors, may be specified by user set for their CPE Creds use, wherein such professors who published relevant Creds that, for example, have sufficiently similarity matched Creds CPE(s) as purpose expressions for Repute Creds and EFs, and/or as purpose expressions for the subject matter of such Repute items (and/or sufficiently similar Creds subject(s) if so specified), and who are employed at "major" globally ranked universities (e.g.
ranked by U.S.
News and World Report) might be employed for aggregate Creds calculation, all the foregoing contributing to the PERCos determination (e.g. by Coherence Services), for example in some embodiments, of a prioritized list of similarity matching of purpose class members based at least in part on such professors aggregated asserted views of sufficiently matching resources and/or portions thereof. Such purpose class member neighborhoods may be similarity matched and/or otherwise filtered, for example, for published purpose class applications that are members of the desired neighborhood set that are sufficiently corresponding to user CPE
and/or components thereof. Such results may be, for example, provided in the form of a priority ranking reflecting the asserted assessment of the specified Repute input arrangement, such as such professors as discussed, who are in, or otherwise associated with, a CPE corresponding purpose class and/or Domain/category set, and who are employed at such globally significant universities. Some of such matching neighborhood, for example purpose class, identified members might be providers of "master" purpose class applications that also provide portion sets focusing on both astro and bio physics, and wherein such subclass arrangement set is of sufficient apparent quality that Repute asserters consistently declare such a given such resource set, and/or resource portion set thereof, as "best of breed" or otherwise highly ranked for the user set for matching the user set CPE (user purpose and purpose include purpose set).
PERCos learning, discovery, and experience enhancement can take various forms, without limitation a few examples of which are:
1. A user set may specify a Prescriptive purpose expression and then initiate a PERCos similarity matching process set evaluating resource store information to, for example, identify a purpose class application. Such purpose class application may then provide an interim result set (which interim result set may or may not be made available to such user) and where such interim result set has been derived from CPE
similarity matching against resource information stores to identify a purpose class set. PERCos processes then may, for example, identify resource member and/or member portions of such purpose class set and may filter and prioritize such members and/or portions in accordance to further similarity matching analysis against respective CPE information of such member set and, if specified, other metadata, for example characterizing and/or contextually important to such members such as member Repute filtering/prioritization in accordance with user CPE
specification, and employing, for example, any auxiliary Dimension information, as specified. A user may then, for example and in some embodiments, select one resource of such members such as a specific purpose class application, and then a further PERCos assisted process set may occur involving user interaction with such selected application purpose class application capabilities. Such further assisted step set may include, for example, further purpose expression specifications by such user using such purpose class applications general and/or Domain and/or more specific tools, which such process set may lead to further information sets that are acquired, for example, one or more applications and/or information sets, for use by user, such information sets being offered as candidate and/or provisioned resources (within and/or associated with the processes of such purpose class application) where such further information sets may identify and/or provision external to such application resource one or more resource sets and/or portions thereof.
2. Alternatively, a user may in some embodiments select a symbol representing a purpose class application wherein such application symbol is, for example, among a set of symbols, such as a plurality of symbols representing different purpose class applications which such user and/or user group (such as such user's corporate and/or divisional and/or department administrator and/or IT manager specified) to populate such user's general, or a purpose class specific computing desktop or window or taskbar or the like. After such selection and associated provisioning, in some embodiments, for example, a PERCos enabled purpose class application may apply PERCos capabilities and processes to support user further purpose specifications and associated resource and/or resource portion selection and associated knowledge learning, discovery, provisioning, user related experiencing, and/or the like.

3. Alternatively, in some embodiments, a user may specify a CPE, wherein a PERCos process set conducts similarity matching against one or more resource characteristic indexes (representing descriptive CPE, any germane metadata, and/ the like) to match, for example, against Master Dimension information, with or without auxiliary Dimension information and/or the like, so as to directly, without the aid of a purpose class arrangement, identify, and for example, prioritize (or otherwise list and/or display) resource set and/or resource portion arrangement set information, for example, for user inspection, evaluation, selection, and/or initiating further PERCos processes to reorder and/or recompile and/or modify criteria for candidate one or more resource and/or resource portion sets.
As discussed, PERCos capabilities in some embodiments can be applied or otherwise integrated into, if desired, computing arrangements in such a manner that PERCos capabilities can be applied to any specifiable purpose type. For example, in such embodiments, a moderately experienced off road bicyclist can employ PERCos to learn about moderate difficulty, not remote, not steep, moderately trafficked, biking trails near the user's new employee location; or a user interested could learn more about differing arguments regarding global warming and associated political action groups and their activities; or a user could learn about avoidance of repetitive wrist injuries when working as a software engineer or about the comparative efficiency of large versus multiple computer displays when working with multiple, large scale documents; or about the relationship between, availability, durability, cost, and shedding of wool v-neck sweater brands; or about contributing to the overall value of the comparative cost of travel, time spent in stores, cost of item, cost related to service and repair and support, for large appliance purchases; or about the technical progress and challenges in using stem cells in treating kidney disease; or about the challenges concerning, and available information regarding, near earth asteroids/comets and human community protective measures; or identifying the six most likely people with whom you could synergistically enjoy listing to classical blues music, or watch and discuss a series of documentaries across multiple sessions employing at least in part use of shared common purpose resources, and wherein PERCos capabilities are supportive of documentary resources identification, prioritization, and selection processes and further chat, video conferencing, and/or other forms of shared, common interest virtual presence and common participation.
In some embodiments, purpose class applications can employ, for example, array and provision resources in support of class related user purposes and can maintain Frameworks populated by purpose class specific resources such as references, videos, games, music, experts, and/or the like, available as managed resource opportunities supported by PERCos operating system, environment, and/or application resource management capabilities. As such, a purpose or more specifically a PSKCNS class on Sport Car Maintenances and Mechanics might have various auto manual and repair handbooks, videos, and other reference resources as well as lists (with or without their Creds as associated with list instances) of Participant Experts associated with the overall CPE set for the class and/or with contributing CPEs associated with class resource instances and/or portions thereof. Also, as such, an environment can be maintained, for example by an affinity group such as a club administrator arrangement and/or commercial and/or nonprofit service wherein a CPE arrangement specific resource rich purpose fulfillment environment is available to participants, and, for example in some embodiments, wherein membership/user of a PSKCNS purpose class application may have requirements such as speaking a certain language, a given degree level generally or in a certain academic area, being an alumnus of a given school or school type such as a nationally ranked university, having a specific or generally having union membership, being a licensed contractor, belonging to a national professional association, being of a certain age, being credential by a reputable credentialing authority, and/or any other logical, and in some embodiments or cases in particular, testable criteria where objective and/or verifiable/testable lists are maintained by, for example, reputable authority entities. This PSKCNS purpose class application "qualifying"
criteria may be proffered by applying participants through PERCos PSKCNS
compliant application forms, and wherein such specific proffered information instances, such as membership in an engineering organization, could be automatically checked against such information stored as information within a PERCos cosmos resource, such as by, for example, PERCos Test and Results Service, and wherein a PERCos form has sufficient field resource related information and associated capabilities such that a response in standardized format to a form question or list, such as membership in the ACLU or NRA or AFLCIO, could be automatically verified as, or flagged as not, true as an EF. Such organizations, including corporations, educational institutions, colleges, clubs, societies, publications, and the like, could provide such characterizing "list" information in a PERCos embodiment compliant or integrated form supporting such automatic identifying and/or validating and/or testing functions. An expanding PERCos resource cosmos would assist in such systemization and normalization of web based networking relationships by enabling use of EFs and Creds to provide users and Stakeholders with sufficient information, similar but in some ways enhanced over, traditional face to face human interactions.
PERCos, for example in some embodiments, can support a coherently ordered social networking arrangement structured at least in part for use with resources and Big Resource environments and enabling groups of people to mutually participate in common purpose computing sessions and/or like interactions with an optimized access to, evaluation of, and/or provisioning of, specific session purpose supporting resource sets, including, for example, participant sets, prioritized, alphabetical, or otherwise organized and particularly suited to a user set CPE
specification. Further, PERCos learning and discovery capabilities should substantially enhance social, knowledge, and commercial networking for many people by providing capabilities for users to learn and discover information regarding resources thereby enlarging user understanding of possible resources, including resource portions, and/or enhancing processes related to such resources.
PERCos can, in some embodiments, help users identify and structure synergistic multi-user arrangements specifically responsive to consonant respective purpose expressions, capabilities, other characteristics, and/or the like so as to form a commonly satisfying purpose fulfillment networking groups suitable for constructive, purpose fulfillment interactivity. PERCos can extend synergism evaluation and cohering processing to optimize matching among both users with other resources supportive of their mutual and/or consonant objectives, including the evaluation and cohering processing of non-Participant resource types in order to provide an optimum environment for shared purpose fulfilling processes. For example, a user set could specify a Contextual Purpose Expression regarding their purpose set (using, for example, Master Dimension specification, with or without auxiliary Dimensions) and PERCos could perform a similarity assessment of declared purpose classes, including, for example, PSKCNS oriented purpose classes or the like, which are, for example, defined/situated in ontology and/or taxonomic structures by Domain experts and/or other Stakeholders for PERCos purposes on behalf of a standards organization such as a PERCos purpose or specifically PSKCNS utility. In some embodiments, such class declarations could, for example, declare that one or more user prescriptive CPEs representative of PSKCNS purposes are associated with, for example, one or more purpose classes, and such expression sets can be used to, at least in part, identify one or more PSKCNS classes.
In some embodiments, such similarity matching of user CPEs to purpose class CPEs, other ontology neighborhoods, and/or resource instance CPEs, PERCos may use resonance resource instance sets, and such sets in some embodiments may, for example, employ purpose optimizing synergizing instructions. PERCos synergizing instructions can represent specifications of resource instance combinations and/or portions thereof where a plurality of resources perform, or may perform, a contributory purposeful one or more functions, for example contribute one or more characteristics strengths as may be specified by their associated CPEs and/or metadata, where such resources may be associated in CPE purpose fulfillment as mutually complementary and/or otherwise advantageous, from a combinatorial standpoint, in realizing, or attempting to realize, a specified purpose Outcome or interim process and/or result.

In some embodiments, PERCOs synergizing to purpose, for example, employs building blocks in the form of resources and/or resource portions, including, for example Constructs, knowledge information, Participants, devices, services, and/or the like, the foregoing representing families of different resource types that may be combined in some manner to optimally assist users in achieving their Outcome objectives by forming particularly productive arrangements for fulfilling, or otherwise attempting to fulfill, one or more CPEs. For example, resource items having differing characteristics might, for example, be useful in the specification of the following CPE: "learn thin film solar cell materials science and fabrication."
In some PERCos embodiments, a publishing or synergizing set specification arrangement may be presented in a format that represents, for example, separate simultaneously displayed, vertical resource type prioritized (in order) characteristic instance choice lists.
Such lists may be prioritized by resource instances being processed through Coherence Services evaluation, such as similarity matching against user and/or related purpose expression sets and/or filtering and/or evaluation based upon Repute Cred assertions and/or Effective Facts and/or other information such as group administrator governance information. For example, in some embodiments, an example list display might comprise, a first column displaying general topic textual-audio-and/or visual reference materials as a category area, a second column representing consulting domain experts (e.g. names) with teaching/tutoring/ skills, a third column representing expert domain researchers that may be available to consult, including doing collaborative work, in the area, a fourth column representing expert manufacturing implementers (practical manufacturing engineers) with applied experience in the domain, a fifth column representing market analysts who have knowledge and experience concerning market interests and considerations, and whereby a user set can evaluate and/or select and/or proceed with further evaluation, discussion, information supplementation, and/or item selection. Such listed information may be complemented by supplementary information where, for example, such specific instance information may be complemented by further, more detailed characteristic related information by a user moving a cursor over a candidate list instance and with instance specific details appearing in an adjacent, well organized "balloon" temporary sub-window, toggled to alternative supplementary window, and/or the like. In this example and embodiment set, selecting instances from such lists of resources, includes, for example, potential Participants having synergistically complementing characteristics who can form a synergistic user group for what a user set, as assisted by their PERCos arrangement, perceives as an optimum Participant candidate synergistic resource combination which may "best" serve as CPE
fulfillment interim and/or Outcome complementary users/contributors. Such tools may also be used with non-participant synergistic resource selection, for example, in the specification of elements of a purpose class application environment where such resources might at least in part be used to populate, for example, a PERCos Framework associated with the user set CPE set (including, for example, a collective, resolved group Purpose Statement) such as, when building a purpose class application like a student integrated syllabus, note writing environment, presenting a synergy arranged faceting list to select a productivity application that that would fill a Framework Role of word processor.
PERCos Repute resources may be particularly useful, in some embodiments and circumstances, in optimally identifying, filtering, and prioritizing candidate and/or to be provisioned resources for PSKCNS. Such Repute resources may, for example, employ EFs that were published as self-describing systematized profile/CV by participants, where, for example, a participant might declare that she is an MIT tenured Associate Professor in Biophysics, aged 53, with x specific and/or number of peer-reviewed authored publications, that she lives in the Boston Metro area, that she is available for online and/or in-person research and development consulting and/or knowledging session participation as PSKCNS group Participant, and that she expects and/or requires a fee of y dollars per hour of session participation and/or consulting. Creds on such professor by other tenured professors in Biophysics may, for example, be used in combination with the professor's declared EF and CV information, such that the combination of such EF and other declared CV information might be used to determine that such professor could be helpful in a given PSKCNS session as a consultant, and such information, along with such Cred assertion information on such professor for such consulting purpose could elevate or downgrade its list ranking position relative to other candidate consulting professors.
Further, in some embodiments, such self-describing systematized profile/CV may include personal information that may in part, or in whole, be included in Creds, including information regarding avocation, such as surfing, mountain climbing, astronomy, car racing and/or the like;
hobbies, such as football, baseball, soccer, rugby, and/or the like; marital status, married, single, divorced; family status: number of children and age and sexual orientation, such as straight, gay, lesbian and/or the like; health status including material medical conditions such as diabetes, arthritis, and/or the like. In some embodiments, such personal information may be in part or all encrypted and rules controlled to contribute to personal policy enforcement regarding privacy of information and with whom any set of such information may be shared. Further, for example, in some embodiments such Creds may store portions of such characteristics information as Cred EF
information, where such information is externally testable and/or verified, for example by a certificate provided by a trusted authority and/or a test procedure set operated with an authority that maintains a PERCos compliant information verification arrangement. For example, a corporate publisher of a Cred may describe their identity in a form which satisfies EF
reliability/testability requirements and may be described in the form of an EF
where such publisher lists, for example, in a web accessible corporate database in a manner satisfying EF
testing, including for example certificates, rules that affirms that the corporation is the publisher of such Cred, encryption techniques, administrative controls, and/or the like.
For another example, a Cred published by a given Participant may contain, or reference, an EF regarding such participant being an employee of Boeing, where such individual is listed as an employee on a publically accessible information listing on a Boeing website in a form compatible with a PERCos EF testing procedures.
In some embodiments, registered or otherwise declared resource members can be stored as accessible information elements within an overall metadata arrangement, where such information elements are, for example, classified as participant members of one or more category types derived at least in part from their employment with or by users, Stakeholders, other resources, and/or the like under one or more specified conditions. For example, a resource may be declared, or by historical usage association be identified as, a resource member of a purpose class, such as, for example, a synthetic biology "DNA reference Library of Functional Units" being used for, and a declared and/or being a historically derived resource member of, the purpose class of "create DNA preparations for tissue replacement" as identified and defined by an authorized Domain experts team for biosciences, while the same purpose class may also have the "Synthetic Biology Institute" at UC Berkeley as a declared and/or historical information derived participant grouping member of such same purpose class, and further, for example, EF
verified or verifiable researchers at such Institute may also be stored as participant members of such class, along with, for example, with their self-assertions and Creds by other parties on their Quality to Purpose for such purpose class. Such metadata information elements can, for example, be associated with resource instances, groups, and/or PSKCNS classes for PS KCNS
purposes.
Participant sets may, in some embodiments for example, declare themselves as resource member participant type instances belonging to one or more purpose classes and/or associated with any one or more purpose class applications as historical users and/or Stakeholders, along, for example in some embodiments, with storing such member instance declarations of their self-assertions and/or third party EF and/or Cred declarations or assertions regarding their expertise level (e.g. beginner, moderate, expert), knowledge level (e.g. modest, medium, high), trustability level (e.g. low, medium, high), experience level with, for example, a purpose class application, and/or the like. In some embodiments, for such declarations to be effective may require satisfaction of certain Expert set, utility set and/or other governing body set, rules, which may include tests for verification purposes, where such as one or more characteristics of participant set correspond to EF and/or Cred criteria, such as a requirement for being a member of a given affinity group, and for example, may include the declaring participant set being comprised of one or more tenured history professors at the University of Maryland, and might further require in certain instances, requiring for example that certificates associated with one or more EF
elements and/or tests that validates the EF requirements, such as looking up a list published by University of Maryland of its tenured history professors and confirming such EF as sufficiently reliable as defined by PERCos arrangement related specifications. The latter may, in some embodiments, might require that the publisher of such be the University of Maryland and that University of Maryland publish such list in a form compatible with one or more PERCos embodiments such that such list can be securely evaluated, queried, and or otherwise tested and/or inspected. Further one or more such embodiments may, for example, require that such test be a sufficiently secure system arrangement in accordance with specifications for communication, testing, and/or security system features attributes (for example, for specified security level and/or other attributes) and whereby, for example, communication protocols, authentication procedures, encryption processes and specifications, information store and/or user access controls, and/or the like meet sufficient standards for a given security level to maintain overall sufficient system authenticity/reliability. Such trusted EF related information may, for example in some embodiments, be used in PERCos identification, evaluation, filtering, prioritization, and/or the like processes.
PERCos classes may, in some embodiments, have resource participant member arrangements wherein participant individuals and/or groups and/or other resource instances and/or groups, associated with one or more resources, such as purpose class applications, could both be available in the form of prioritized lists of such member types, based for example on Repute input, as may be managed, for example, at least in part by a cloud utility and/or an administering expert set. For example, in some embodiments such resource sets may be prioritized and/or otherwise evaluated in relationship, for example, to a participant history related to any given CPE use and/or through the use of Stakeholders Repute Cred third party assertions as related to such Participant Quality to Purpose, Quality to Value, Quality to Contribution to Purpose, and/or the like use of any given CPE and/or associated purpose class applications and/or as associated with purpose classes and/or interactions with other participants and/or Stakeholders, for example, as may be associated with foregoing. For example, such evaluation may reflect such participant performance as a user regarding such user's Quality to Contribution to Purpose in one or more common purpose computing sessions, and/or the like, and where Quality to Contribution to Purpose Cred information may be aggregated across various similar purposes to represent a Quality to Purpose rating for a higher order (such as a superclass) purpose class or purpose neighborhood. In some embodiments, such evaluation and information use may be applied, as applicable, to any resource instance and/or group in relationship to any other resource instance and/or group, that is for example, a given information resource may be evaluated as to Quality of Contribution to Purpose if the resource serves as a contributing component in a CPE fulfillment process.
PERCos purpose class members could be, for example in some embodiments, at least in part be comprised of a list, subclass, or other grouping sets of resource members in accordance with their types, such as participants, information reference resources, purpose class applications, Informal resources, cloud services, devices, computing platforms, Frameworks, Foundations, CPEs, and/or the like, along with their associated Creds, EFs, and/or any other associated metadata. Such class type members might further and/or alternatively comprise, in some embodiments, for example, Constructs, participants, tangible resources, and/or published CPE
instances and/or sets, and/or the like. In some embodiments these class members can be organized and manipulated by type and by type combinations, for example, generally by resource, by participant, and/or by purpose class other associations of an instance or type. The foregoing may be manipulatable both separately and in combination to, for example, enable users and/or PERCos arrangements to, at least in part, assess resources for their historical associations and/or their Repute Quality to Purpose or Quality to Contribution to Purpose performance and/or relationship (expressed, for example as Creds), and/or the like. This assessment may be performed, at least in part by, for example, evaluating Creds and/or EFs, and/or by evaluating Outcomes resulting at least in part from the use of certain resource sets as contributing components to other resources sets such as by being contributing participants, CPEs, Constructs, and/or the like, and, for example as operating in purpose class applications or other Framework roles. Such evaluation information facilitates the evaluation by user, Stakeholders, and/or PERCos arrangements regarding the conditions and characteristics of working with different resource sets.

With some PERCos embodiments, users can identify, evaluate, filter, prioritize, and/or select member resource combinations that may respectively define resource networking component "spaces", such as Hilbert spaces and/or the like. Much like PERCos Dimension CPE spaces, some PERCos embodiments enable users and PERCos computing arrangements to adjust such resource spaces to provide differing views into resource and resource portion sets so as to facilitate user and/or PERCos arrangement evaluation for purpose fulfillment options. By supporting user sets using, administrating, and/or manipulating PERCos information resources, including EFs and Quality to Purpose and/or, for example, other "Quality"
Repute factors related to participants, published CPEs, and/or other resources and/or resource portions, for example in some embodiments, user sets may direct PERCos capabilities, through, for example, Master and/or auxiliary Dimension PERCos specifications, to produce viewable and manipulatable sets of candidate participants and/or other support resources for PERCos session purpose fulfillment. For example, this ability to view and manipulate purpose fulfillment resource spaces can inform users regarding the relationships between a resource set characteristics and various purpose expressions such as Core Purposes, other CPEs, and Purpose Statements and their desirable (or undesirable) characteristics. This can facilitate user assessment from historical, Repute information, and/or the like perspectives, regarding working with specific resource set(s). In some embodiments, by viewing Quality to Purpose, Quality to Value, Quality to Contribution to Purpose, and/or other Cred Repute assessments and EF
considerations in combination with underlying purpose expression(s), one can calculate corresponding spaces that may then be used for assessing resource instance and/or resource combinations as to their differing relationships to such different purpose expressions and their possible relationship to such purpose expressions respective fulfillment, that is, such spaces may be assessed as to how they may correspond to desired Outcomes.
In some embodiments, PERCos session historical information may be stored where such information, for example, may be associated with resources, such as purpose class applications and/or participants and/or CPEs and/or other resource instances and/or purpose classes and/or other ontological groupings and/or the like, associating for example, chat, texting, blog, comment, edit, video conferencing, and/or the like activity types. Such information may be stored, for example, for use in any combination at some later time in association with, for example, such later current user purpose and/or Core Focus expression related PERCos activities. Such information type(s) may be associated with any specific and/or combination of such PERCos class member types, for example, where such member sets are members of PERCos class type that may be similarity matched with current user CPE set.
Such historical information may, for example, be published in the form of a resource set as individual instances of associations with a specified purpose class, where such resource set may be "reused" as a social, commercial, and/or knowledge information asset set, for example, during, aiding, and/or otherwise being made available during, a PERCos session and/or other employed for commercial and/or social reasons, such as for information aggregation and advertising/promotional information marketing and use. For example, a multi-media video of a physics teaching session may be published as a resource associated with a CPE
set and where, for example, such resource includes a table of contents and a contents index, and further where users in a PERCos enabled session may employ during such session a portion of such resource as may have been published associated with a CPE set for such portion as a result of previous usage (or Stakeholder declaration) of such portion for such purpose, and where any given portion associated CPE may be a subclass of a CPE, or a CPE set, for such multi-media video.
Such resource information, that is the association of a portion set of a resource with a CPE set may be published in the form of their respective resource types, subtypes, aggregations, and/or any other logical information forms and/or combinations, where such information is associated with a specific given resource, resource combination, and/or portion, so as to be available for evaluation and/or processing purposes at some one or more later times.
In some embodiments, Repute is a core PERCos capability set providing powerful purpose computing tools for filtering through huge candidate resource sets based on reputation and relevancy related attributes and assertions. Repute can be used to evaluate, and/or, for example, to filter, sort, prioritize, and/or otherwise aid in the arrangement of candidate resources identified among large resource arrays to produce usefulness optimized and/or otherwise prioritized candidate results. These results can be based, at least in part, upon Repute attributes as they may relate to the apparent contextually related "qualities" of such resources ¨ that is resource sets may be measured, at least in part, by quality of performance/usefulness and/or other germane indicators interpreted through the use of related contextually significant attributes, providing assessments of resource reputation as related to user purpose sets.
Repute results are produced by augmenting prescriptive and descriptive CPEs or Core Focuses with attributes and any associated values that are descriptive of the "quality" variables to be used in the relative assessment of, and frequently, comparative relative usefulness, of purpose fulfillment resources, and where such quality variables are informing regarding the possible relative potential usefulness of the subject matter of resources and/or resource portions, calculated employing such reputational relevant fact and/or assertion stipulations. Such stipulations can be expressed, for example, through (a) the expression of CPEs, (b) stipulated by non-CPE metadata, (c) otherwise expressed through one or more preferences and/or profile settings including any governance sets, and/or otherwise historically, rules based, published, and/or contextually derived information. Such Repute resource organizing calculations may, for example, contribute to the filtering and/or in some other manner order one or more useful or possibly useful resources using assertions and/or facts that have been expressed employing and/or translated into standardized characteristic elements along with any applicable corresponding values.
Repute has three main specification groupings, Effective Facts, Faith Facts, and Creds. EF
specifications contain "ascertained" and/or otherwise contributed factual assertions regarding a subject, such as the date a person was born or an institution's assertion that an individual is an employee and, for example, holds a certain position and/or title. Faith Facts are based upon spiritual beliefs and not subject to the testing and/or trusted authority rigor of Effective Facts, but may involve testing and/or validation/certification by a spiritual authority associated with the FF associated spiritual belief group. By contrast Creds contain and represent assertions, rather than settled or settable facts; such assertions are made by one or more parties that have respectively, at least one persistent, operatively unique identity, and where such assertions do not rise to the level of a factual attribute set that was stipulated by a reliable, recognized unbiased fact related "authority" of sufficient reliability as to the fact, as least under certain conditions. In some embodiments, EFs, FFs, and Creds have an identified subject matter characterization set. In some embodiments EFs, FFs, and Creds may require that certain information related to any one or more such subject matter characteristics sets or portions thereof, such as a persistent one or more identities to be associated to any of subject matter publisher(s), creator(s), provider(s), as well as in some embodiments providing one or more of:
location(s), time(s), date(s), authoring and/or publishing id(s) and/or any other identifiable and inter-operably interpretable associated other characteristics desired or required by an embodiment, and where any one or more of such subject matter characteristics may be required to be reliably known (e.g. certified) and/or were otherwise testable, that is as Repute information related characterizing the subject's topic matter and/or any one or more other Repute related characteristic(s) related thereto. By contrast with EFs and FFs, in some embodiments, Cred subject matter may either not have a persistent one or more identities as generally meant herein regarding asserter identities, that is Cred subject matter may correspond to a user resource class, some affinity group, or some other logical grouping that, for example, may provide an group identity, or the subject matter may be explicitly identified through the use of a user resource and its associated UID, and/or otherwise may be a topic, such as a generalization, which, for example, is provided by a Cred publisher with a operatively, or sufficiently as may be prescribed under the circumstances, distinctive to unique ID, such as a web page address, or a taxonomic id created by such publisher/asserter. Persistent subject and/or publisher, creator, provider, and/or asserter identity(s) may contribute to a Creds trust and/or integrity level, and/or other characteristic representation(s), of Cred applicability, authority, and/or reliability.
Some PERCos embodiments will treat an expression of a subject characteristic as a fact, not an assertion, when such expression was made by a party having specific and convincing authority to declare a fact, such as an EF or Ft, regarding a subject. Such interpretation of specific and convincing authority may be contextually dependent, for example, as related to topic and/or other assertion characteristic(s). By contrast, Creds represent assertions that may be generally recognized, or for example, disputed, and are expressed opinions regarding subjects and such assertions are not demonstrable as facts by reasonable testing. EFs, FFs, and Creds may be deployed according to reliability levels. Reliability levels can inform user(s) and/or associated computing resources (such as an operating PERCos session) as to whether a given degree of specified reliability satisfies either preset and/or current session rules and/or other criteria as to specified reliability. For example, in some embodiments, a user may be presented with the option to select from levels 1-10 reflecting the underlying level of EF or FF
fact testing, such as related security procedures and/or the representing assessed (for example by a PERCos utility or other administering body) authorities reliability in authenticating such facts.
EFs, FFs, and Creds can form, for example, filtering "vectors" that complement PERCos Core Purpose and other purpose expressions. They provide further, and in certain embodiments and/or circumstances primary, filtering and/or prioritizing input. In part as a result of the use of standardized purpose Repute expression specifications and related values reflecting factual and/or assertion characteristics of Repute subjects, Repute variables provide input for the calculation of results that can most closely correspond to, and/or otherwise implement and/or optimize, results related to the objectives of CPEs and any associated preferences, rules, historical information contributions, and/or the like. In use, EFs, FFs, and Creds may be used in combination, either with their own type (e.g. EFs with EFs) and/or in combination with the other type (e.g. EFs with Creds), and Creds, singularly, or in some combination, may be in some embodiments aggregated and/or otherwise algorithmically interpreted and associated as inter-operably interpretable values with any resource by, in part, the association of Repute information with the subject matter of such resource, and/or by association with any one or more resource characteristics, such as with one or more resource publishers, providers and/or creators and/or, for example, as associated with a performance characteristic of the subject matter, such as the reliability of a certain type of hardware memory for a certain type of fault tolerant application class. In such an instance, a purpose class CPE for employing fault tolerant hardware memory that contained fault tolerance as an expression subset might, in a given application, be employed in matching with resources and/or resource portions in a manner where the fault tolerance expression was matched against the stored information regarding asserted fault tolerance quality(ies) of a given resource set in a manner whereby resources were prioritized, at least in part, in accordance with the assertion by certain qualified experts. Such experts may be determined according, for example, to user(s) specification, and/or, for example, third party authority organizations such as certifying authorities and/or, for further example, by known generally assumed to be useful asserters, such as senior faculty members at institutions who are accepted as Domain experts, and/or as asserted by qualified asserter for the purpose such as an associated society or other Affinity Groups.
Some PERCos Cred embodiments may be organized as:
1. A Cred may have one primary operatively unique, identified subject matter regarding which an asserter is making an assertion, such as "Oxford Shorter English Dictionary" "Microsoft PowerPoint" "Wild Caught Salmon" or "President Bill Clinton". The first two can readily be identified by providing a unique naming identity for specific resource product, or for example, a PERCos disambiguation web service, for example, could provide assistance to a user set, such as providing a drop down suggestion list or other faceting list interface providing context specific appropriate specific options and/or clarifying category instances for users to select, for example, Microsoft PowerPoint 2010, with the service providing the explicit Microsoft (or other party) unique identity for such specific product by inserting it into an appropriate Cred item information space in, for example, a PERCos compliant form.
2. A Cred has one asserter, an aggregate Cred has a plurality of asserters, a compound Cred has a plurality of Creds (at least information wise, but may not be stored as discrete, individual items) and may or may not have a plurality of asserters.
An asserter may be an individual person, a group of persons acting as a named group such as a club, or another form of organization such as a corporation, government, or the like.
3. A Cred or aggregate Cred or compound Cred has a Stakeholder publisher set, but in some embodiments if publisher set is the same as the asserter set, it may not need to be separately stored or indicated as such.

4. A Cred or aggregate or compound Cred may have a provider set as well as a publisher set, but in some embodiments if the provider set is the same as the publisher set or asserter set, it may not need to be separately stored or indicated as such 5. A Cred has as its subject a resource section including at least one identified resource that is persistently identifiable (may be a PERCos or non-PERCos resource), and further it has a resource set associated at least one CPE and at minimum, at least one Quality to Purpose, Quality to Value, or like standardized Repute assertion type, with the association of an interoperable interpretable value, for example, a user definable value, for example a 17 on a scale of 1 to 20. For convenience, in some embodiments a Cred may have multiple resources as subject contents, but only one CPE by which each resource is assessed as to its Quality to (that) Purpose.
Plural Creds may be published in a compound Cred, which may be organized by a purpose class arrangement and/or other ontology set.
6. A Cred may have one or more validation rule sets validating that such assertion set was made by such asserter set, such validation rule set employed to perform a Cred information validation unless, under some circumstances and embodiments, the Cred has a trust certificate, and/or the like, issued by such asserter set for each assertion and/or for each aggregation of such assertions, and/or such Cred has a certificate issued by a trusted party, all the foregoing in accordance with Cred rules for the embodiment and/or circumstance of embodiment use. Such same validation sets may be, in some circumstances and/or embodiments, applied to Cred publishers, providers, and/or other associated parties. Such use may include, for example, the selection by user and/or Stakeholder sets of a trust level associated with such Cred type and/or circumstance of use in PERCos processes, such as a Cred type level 5, in a 1 ¨ 5 schema where 5 is the highest level of trust, and where such schemas may require either or both of a secure, encrypted hash certificate set for such Cred stipulation information issued by such publisher set and/or asserter set and/or provider set supporting a secured fact test procedure employing, for example, encrypted communications between a user PERCos arrangement and a trusted server operated by such respective one or more members of publisher, asserter, and/or provider set, whereby such fact or fact set and/or related information may be securely confirmed by such one or more Cred value chain participants.
7. A counterpoint Cred may include and/or reference a Cred where such counterpoint Cred was specifically formulated to correspond to such referenced Cred, wherein both such counterpoint Cred and such referenced Cred have said same subject matter set, either directly or approximately and where such counterpoint Cred employs the CPE set, either directly or approximately, of such referenced Cred, and further provides differing one or more assertions comprising a differing assertion set, and further providing information directly indicating, including some form of referencing, that such counterpoint Cred provides an alternative assessment of such referenced Cred. For example, in some embodiments, a counterpoint Cred will employ the same assertion Facet set, such as Quality to Purpose, but with a different associated ranking value, such as 2 out of 10 versus, in such an embodiment, a more positive 8 out of 10. Plural counterpoint Creds satisfying the conditions of an aggregated may be provided in counterpoint aggregated Cred form. Counterpoint Creds may be combined with their associated Creds in compound Creds.
8. A Compound Cred is comprised of multiple asserters collectively providing their assertions regarding the same Cred subject matter, but employing, for at least in part for a subset of such assertions, differing Facet sets and/or the same Facet sets but differing assertion sets regarding such assessment sets.
9. An Aggregate Cred provides one or more aggregate values for shared Repute Facet values such as combined assertion ratings (e.g., an average value such as 7 out of 10) for a Quality to Purpose Facet for 'Learning' 'General Reference Encyclopedia' for Wikipedia, or for a hypothetical purpose class application for a recent quarterly publication "Online Update for Applied Synthetic Biology" article on Skin Tissue Replacement located through a PERCos learning Big Resource query.
10. A Cred may reference and/or include one or more other Creds that employ such Cred, and/or such Cred's asserter, publisher set, and/or provider set, as the subject matter of such other Creds. Further, a Cred may reference and/or include one or more EFs and/or FFs. Such EFs and/or FFs information may be the subject of one or more other Creds. Such referencing and/or including Cred may reference and/or include such other Cred's information regarding such EF and/or FF
characteristics, providing assertion information as to whether such EF and/or FF
characteristics are true or false.
Appendix B illustrates a non-limiting sample embodiment of a resource Repute Cred's information element types.
Appendix C illustrates a non-limiting sample embodiment of certain Repute Cred instance types standardized and optional information elements. In this embodiment, Compound and Complex Creds may include one or more of the features of Aggregate Creds, as may be applicable.
Some PERCos EF embodiments may be organized as:
1. An EF may have one primary operatively unique identified subject matter that is stated as true or false based on whether it is stipulated to be a settled fact e.g. John Doe is a tenured professor at MIT.
2. An EF may have plural subsidiary operatively unique identified subject matters that are individually stated as true or false based on whether each, respectively, is stipulated as a settled fact, but each such subject matter shall be a subclass of the primary subject matter.
3. An EF may have one or plural, individually identified stipulators, but such stipulator set shall be the same for each and every subject matter stipulation. A
stipulator may be an individual person, a group of persons acting as a named group such as a club, or another form of organization such as a corporation, government, or the like.
4. An EF has a publisher set, which in some embodiments may not need to be separately stored or indicated if the same as the stipulator set or not otherwise required.

5. An EF has a provider set, which in some embodiments may not need to be separately stored or indicated if the same as the stipulator or publisher set(s) or not otherwise required.
6. An EF may have one or more validation rule sets validating that such assertion was made by such stipulator set, such validation rule set employed to perform an EF
information validation unless, under some circumstances and embodiments the EF

has a trust certificate issued by such stipulator and/or stipulator set for each assertion and/or for each aggregation of such assertions, and/or such Cred has a certificate issued by a trusted party, all the foregoing in accordance with EF rules for the embodiment and/or circumstance of embodiment use. Such use may include, for example, the selection by user and/or Stakeholder sets of a trust level associated with such EF type and/or circumstance of use in PERCos processes, such as an EF
type level 5, in a 1 ¨ 5 schema where 5 is the highest level of trust, and where such schemas may require, for example, a secure, encrypted hash certificate set for such EF stipulation information issued by such validator and/or publisher set and/or a trusted agent and/or stipulator set and/or provider set supporting a secured fact test procedure employing, for example and as may be required in an embodiment, encrypted communications between a user PERCos arrangement and a trusted server operated by such respective one or more members of publisher, stipulator, provider, and/or associated agent set, whereby such fact or fact set and/or related information may be securely confirmed by such one or more EF value chain participants and/or an authorized, trusted agent.
Some PERCos FF embodiments may be organized as:
1. An FF may have one primary operatively unique identified subject matter that is stated as true or false based on whether it is declared to be a settled faith fact e.g.
Jesus Christ is the son of God.

2. An FF may have plural subsidiary operatively unique identified subject matters that are individually stated as true or false based on whether each, respectively, is stipulated as a settled faith fact, but each such subject matter shall be a subclass of the primary subject matter.
3. An FF may have one or plural individually identified declarers, but such declarer set shall be the same for each and every subject matter declaration. An FF shall have a referenced spiritual group, e.g. the Catholic Church, that proclaims such faith fact to be true and such spiritual group shall be at least one of such one or plural declarers.
4. An FF may have one or plural, individually identified publishers and/or providers.
5. An FF may have a provider set, which in some embodiments may not need to be separately stored or indicated if the same as the stipulator or publisher set(s) or not otherwise required.
6. An FF may have a referenced set of operatively identified spiritual source set, such as the King James Bible.
7. An FF may require, and use, any combination of the validation techniques described for EFs.
EFs and Creds and associated PERCos processing arrangements, in some embodiments, employ security tamper resistance technology, such as encryption encoding, secure digital rights management for secure rules governance, hardware tamper resistant processing and memory space for decryption and/or rules processing, and/or the like, the foregoing to help ensure that their respective fact verification and assertion information reliably represents their original published states.
Cred and EF subject matter, in some embodiments, have unique identities. Such identities can be important in ensuring that assertions and fact declarations are associated with the proper locater subject identities in order to facilitate proper, explicit, unique identification of a subject matter instance so that Cred assertions and EF fact declarations can be appropriately organized, aggregated, analyzed, and are properly associated, as may be desired for example, with CPE, purpose, Domain category, and/or resource, instances and/or classes and/or the like. Such unique identities help ensure that parties may, as desired, comment reliably on the intended subject matter and that it appropriately corresponds to the subject matter specification of the corresponding Repute Cred or EF.
Such identities may be associated with specific PERCos Repute Facet standardized and interoperable characteristic approximations, for example, in some embodiments, Facets such as Quality to Purpose, Cost Value as to Purpose, and Reliability to Purpose (including, for example correctness of subject's content, when applicable, or reliability of a device, when applicable, and/or the like), and/or Integrity as to Purpose.
In some embodiments, Repute variables such as Quality to Purpose values as associated with experts, and resources, may be specified as to be applied to an associated specified purpose class set for similarity matching, filtering, prioritization, and/or evaluation processes, when performed. Further Repute specifications may be applied during a user specified PERCos session, where such may be incorporated into Frameworks, Foundations, resonances, and/or other applicable resource purpose specifications, and/or may, for example, be referenced as and operate as underlying preference variables that may be automatically associated with purpose expressions and/or class sets for employment in sifting through and/or prioritizing resources and/or the like.
Repute may provide a resource management set of capabilities and specifications. Such PERCos technologies can provide specifications for resources that describe relevant attributes of resources in the form of standardized categories and any associated values, such information for "assessing" and "valuing" resources as resource candidates for fulfillment of purpose expressions where such details are, at least in part in some embodiments based upon:

(a) known and/or knowable facts, declared by one or more fact determining source and/or by fact verification testing (e.g. checking with a determining source or determining by reading, for example, and verifying author, employer, publisher, file size, page length, location, language employed, watermarks/fingerprints, and/or the like) and/or other assessing that such fact source has been certified as a fact, and/or the like, and where any such EF facts may have an estimated degree of accuracy, for example, expressed as a machine and/or user interpretable value ¨ for example the author of a resource is stipulated as a senior tenured professor at MIT in a domain relevant to satisfaction of a purpose instruction set where such stipulation is through MIT publishing and/or certifying such stipulation and/or where such stipulation is "located" on an MIT administrative website and/or otherwise tested, and where such testing and/or certification may be for example, performed by an authority/fact integrity cloud service testing, which may test for example, the certificates, fingerprints/watermarks, length (pages, bytes) complexity, subject matter correspondence, security (e.g. absence of malware), author, publisher, and/or the like characteristics associated with candidate resources.
(b) interoperably assessable assertions by any one or more parties (e.g. as by parties who have a persistent, testable ID) regarding one or more resources and/or their providers, creators, publishers, and/or other related Stakeholders), for example asserted by senior tenured same Domain colleagues at Stanford, Princeton, Harvard, and Cal Tech that have, for example, rated the resource as highly useful for an expressed user purpose, one or more similar expressed purposes, and/or one or more associated/related purpose classes and/or have rated the author/professor as highly capable associated with the expressed purpose(s).
Such assertions, for example, may alternatively or also include in some embodiments assertions by other parties, for example by a broader body of generally acknowledged (specified by type characteristics) Domain experts, including expressing individually and/or through simple and/or more complex algorithmic aggregations of values associated with a specified degree of value/expertise that are, for example, associated with expressed purpose(s) as associated with resource sets and/or creators and/or publishers and/or the like.
Repute resources further support, and in some embodiments may include applications, services, plug-in capabilities and the like that enable real-time human interaction between disparately located people, in particular providing evaluation and/or specialized monitoring capabilities regarding participant candidates and/or active participants with whom a user has little or no familiarity, but who offers to others (and/or between each other and/or is a candidate for) knowledge, expertise, instructional ability, companionship, entertainment interaction, friendship/companionship, and/or commercial opportunity, and where Repute can help users to determine whether such interaction involves participants who meet and/or exceed pre-set and/or currently selected user set and/or other user associated criteria (e.g. user employer and/or association parameters), including specific, relative, and/or otherwise algorithmically and/or historically influenced criteria. These capabilities may, for example, operate substantially based on stored information provided by web one or more services and/or may at least in part be extracted from effectively real-time biometric related evaluation of session participant behavior, as may be further evaluated through Repute information. These applications and services can greatly facilitate user and/or system identification, filtering, and/or prioritization of at least in part unfamiliar one or more candidate(s) for session participation and/or otherwise initiate and/or monitor a session employing one or more such candidates, participants, or PERCos session users.
Information and algorithmic resources supporting such PERCos capabilities, such as Creds assertion and assessment infrastructure, can, in some embodiments, provide a global system for standardized categories and value expressions stipulated by persistently identifiable asserters as descriptive evaluations of any subject matter, either as general assertions and/or as assertions associated with one or more instances and/or classes of purpose expressions, activities, tasks, groups, and/or other individual and/or ontologically and/or taxonomically organized items, and where such Creds themselves may be organized in ontologies and/or taxonomies and/or other organizing systems such as indexed and relational databases and/or the like.
Creds subjects may include specific Creds or classes or other reliably identifiable groupings of Creds, that is any asserter may make one or more assertions about any subject matter, including Creds sets, creating Creds on Creds, that is Creds expressing aggregates of assertions and associated values reflecting asserters' views of the qualities of one or more, such as a group, of Creds asserted, by, for example, a particular individual, organization, collection of parties, and/or the like, as to a particular subject matter area. With Creds, an asserter may, for example, use selected standardized variables, for example asserting relative values, either employing positive, or positive, neutral, and negative, values. Combined with other aspects of Repute, such as EF
characteristics and values reflecting claims relevant to the importance, relevance, and/or usefulness of individuals or groups based upon facts and/or apparent facts associated such individuals or groups, Repute provides an unprecedented capacity to identify and organize resource possibilities from Big Data and Big Resource.
In some embodiments Cred asserters, may be evaluated by other Cred asserters regarding, for example, their professional credentials, schooling background, credit worthiness, age, location, affiliations, associations (including with individuals), historical behavior, for example as associated with any purpose or activity instance and/or group set. In some embodiments, PERCos services can calculate and display, and/or employ specific and/or aggregate, values for standardized characteristics and/or standardized aggregation of characteristics, by, for example, displaying one or more values (e.g. a value or a value range) associated with each characteristic and/or aggregation, and wherein any such characteristic and/or aggregation may be associated with a task, historical activity, resource and/or purpose expression, instance, and/or class and/or the like. This allows users, for example, based on pre-set preferences and/or at least in part historically based actions and/or related results, to evaluate individuals and/or groups of individuals having, and/or who are otherwise associated with, any such characteristics and values.
PERCos can, in some embodiments, through its Cred, EF, and/or FF capabilities (as appropriate), evaluate candidate participants as to their satisfaction of user and/or user's group criteria regarding participation in a given context/computing scenario.
Standardized characteristics, can include such variables as might be found in a curriculum vitae such as educational related background (including study and/or degree related details such as type, field(s), historical timing including dates and duration such as for employment, schooling (e.g.
years at a college), language(s) spoken, work background (including job title(s), salary(ies), associated dates and durations, employment locations(s) related associated facts such as associated accomplishments, e.g. meeting a dollar amount for sales, profitability, revenue, number of people managed, details related to areas of responsibility such as product and/or services categories, specific instances, and/or related info such as innovations), family background such as childhood family including relatives names, information related to such relatives, military and/or other public service background (such as rank(s), time(s) and dates and duration(s), posting locations, and/or the like). Such Repute variable characteristics and/or values, including any Cred characteristics and/or values (for example values as may be associated with a given CPE or other purpose expression for example, as value associated with having been a military general in a given military service as associated to a CPE related to military strategy determination), may be algorithmically processed and/or combined with any Cred characteristics and values to produce relative measures of appropriateness/usefulness/adequateness.
Social, commercial, and knowledge networking services are tools for users and as such they may best perform when they are structured to be specifically responsive to user purpose and have the capability to support such specification. This enables such a service to provide experience/results that may be substantially relevant and productive. Enabling individuals to constructively and systematically reach beyond their milieu may enable, on the whole, a substantial improvement in the nature of social networking. Towards this end, the role of purpose domain experts and/or administrators may be key to attenuating or eliminating the stream of often marginally thoughtful and/or relevant communications provided by parties participating in chat and other group, topically oriented environments. PERCos Repute capabilities can contribute considerable advantages to participants in social networking activities, particularly in group contexts. The use of EF filtering as to facts related to an individual ¨ that the individual is a certified plumber, an officer in the U.S. Navy, a mathematics teacher, a physician, a theoretical physicist ¨ can matter a great deal in how their participation affects the quality of, and whether in a given instance they should participate in, social, knowledge, and/or commercial interactions.

Repute EFs, FFs, and Cred assertions provide input information regarding individual and/or group sets concerning how and/or whether such individual and/or group sets should participate in common purpose computing session sets, that is the quality, relevance, usefulness, and/or the like of such participation. These capabilities can significantly influence how satisfying and productive such common purpose interaction may be. By organizing participants as resources associated with purpose classes, by being able to filter individuals based on their characteristics including EF and Creds, by having purpose administrators and/or collective group management arrangements and/or the like, through which rules of conduct can be enforced, such as the nature and/or quality of communications by a participant set, so as to ensure, in a manner not dissimilar to human traditional physical interaction scenarios, that who participates is evaluated and often understood, that participant conduct may be managed when necessary, and that social, commercial, and knowledge networking is satisfying, appealing, productive, and/or enhancing, as considered appropriate. For example, a licensed veterinarian who is EF
declared as a veterinarian and has received high marks through Cred assertions regarding skills in treating behavioral problems in cats is likely to be more useful in participating in a think session responsive to a CPE 'learn' (or 'treat') 'housecat behavior problems' than a licensed taxi driver who is more interested in discussing traffic difficulties in a big city or action movies and how they may affect people's conduct when they leave the theater and take a cab.
In some embodiments, PERCos may manage a resource type as published participant resources, such as self-Creds that include self-characterizations by, for example, a veterinarian and/or connected-Creds by such veterinarian's clinic/employer/administrator, and/or unconnected (no or minimal conflict of interest) Creds by such veterinarian's veterinary school that he/she is licensed and, for example, has further credentialed graduate work specialty training in treating behavior problems in cats and dogs. Further, Creds may be supplied regarding the veterinarian providing assertions by other EF "verified" veterinarians and/or veterinarian associated groups, and/or by asserting client cat owners and/or their, for example, EF verified cat owning clubs and/or associations and/or the like. Such Creds may be, for example, in the form of differing aggregate ratings of assertions by asserting type such that, for example, a veterinarian is rated a 7 out of possible 10 for the purpose of treating cat behavioral problems by other veterinarians, 9 out of 10 by clients, 8 out of 10 by several professors of veterinary medicine at U.S. accredited by the AVMA (American Veterinary Medical Association), all the former, for example in some embodiments, stored and available for Coherence processing in aggregate and/or individual instance form for each set of asserting type so that a user set can review at least in part their (the Creds) respective evaluative assertion by type characteristics of asserter.
In some embodiments, exclusion, inclusion, prioritization, and/or other evaluation of possible and/or otherwise candidate resources may be performed depending on whether one or more integrity levels for reliability of information of respective and/or groupings of EF types specified in a CPE set are satisfied, such that user and/or Stakeholder sets instructions (including EF types for Cred asserters, providers, publishers, and/or the like), may be performed as may be required by such user and/or Stakeholder set CPE sets, user stored preferences, user group administrator governance sets, sovereign government instruction sets, and/or the like contributing specifications. In some embodiments, such types may be declared and established as a standard, when specified by Domain and/or general experts, for example, as employed by and/or consulting to a PERCos authority/utility set and/or by one or more Domain associations (such as the AVMA) and/or the like.
Tests may be available to, and/or certificates may be provided by one or more authorities, such as a PERCos one or more utilities, and/or other cloud services, to specifically support the assuring of a user and/or Stakeholder that they may trust, that is find sufficiently reliable for a given purpose class or overall, for example, an EF type declared attribute, such as being a graduate of a given University in a given academic area having a certain degree granted on a specific date in time or the like, however single or multi-faceted. Certain of such type information, such as having an EE bachelor degree, may be standardized, whereas the naming of a subspecialty to a degree may, in some embodiments, be stored as metadata but not be standardized as a subcategory for PERCos approximation efficiency and/or other PERCos embodiment reasons. A user may have, for example, specified in their CPE set or associated Purpose Statement to use all primary expert defined types by averaging all specified type category scores, by averaging and processing some but separately processing one or more others as distinct input, by associating one or more weights with any of these type values, and where the types, for example, provide, for example through a standards body or utility or commercial cloud service set, one or more specific forms of associated authenticating certificates and/or other validation for their respective types, as they may be governed in differing manners.
For example, in some embodiments, a user set may wish a breadth of applicable expert input regarding an economics related learning purpose. Such user set may then provide their specification of associated EF participant asserters as professors of international economics at accredited north American universities, staff columnists at major economics related publications (e.g. Economist, NY Times, Wall Street Journal, and/or the like), federal government economics officials, and economists at major economic think tanks and consulting firms, and/or economists at certain significant corporations, and where one or more of the foregoing subtypes may be certified for authentication by an association, such as the AEA. The AEA
itself, may for example, publish resources comprising such type arrangements to enable users to input into purpose similarity matching standardized Repute attributes for optimizing the level of expert input into an economics related purpose fulfillment process. As with the AEA, other affinity groups, standards authorities, and/or other Stakeholders may publish, for example, purpose class specific expertise type and subtype arrangements, including any differing one or more weightings for such subtypes, for example, as may be related to a purpose class or expression instance. As a result, affinity groups may, for example, publish standards employing Domain or general expert characterizations that are organized in simplified, constrained choice, standardized form in support of interoperability, ease of use, and approximation computing processes. In some embodiments, these standardized type and subtype arrangements may represent implementations by experts and/or authorities of constrained category types associated with Core Purpose, other CPEs, and/or purpose classes and/or other logical taxonomic and/or ontological groupings. These constrained choice sets may, for example, function as Repute (EF
& Cred) and/or other resource related characteristics employed for evaluation, filtering, prioritizing and/or other ranking of candidate resources, for example, within a specified purpose class set or other neighborhood set.
The foregoing Repute formulations may be used as contributing (or as may be edited or otherwise transformed) specification information, for example, to user sets prescriptive CPE
formulation and/or to Coherence processing (and/or otherwise to user and/or Stakeholder evaluation), with such information being processed as input along with any other specified Cred and/or Aggregate Cred instances and any other CPE expression elements.
Such types can be provided, for example in certain embodiments, by a faceting interface listing the constrained number of type options which may be selected to be used individually and/or in any collective arrangement, and which such user may be selecting from during CPE
specification arrangement and/or may have been selected by a previous preference selection process associated with a purpose class and/or CPE set and/or resource set and which may have been stored as part of a user set preference set. Domain and/or general purpose PERCos specific experts may identify, based on Core Purpose, on Domain category (including subcategory) and/or on other combinations of CPE elements, what types may be logically, or with such reasonable frequency, or as sufficient as a generalizing approximation, to be available for user selection, for example from a faceting prompt, and/or for user typed entry, and/or the like. For example, in a situation where the category is, for example, newspaper reporter or college professor, an expert group can declare x number of subtypes, such as a constrained number (e.g.
5, 12, 18, 30, or the like) of different categories, wherein such subcategories may serve as sufficient generalizations/simplifications representing coverage of differing variety of associated real world types. For example, a category for Professor of Wildlife Science, for EF specification purposes, might include, real world department names of Wildlife Science, Wildlife Ecology, Environmental Biology Management, and/or the like. Such type value arrangements systematize important PERCos related characteristics enabling efficient, for example, filtering, ease of user understanding and use and their effects, and appropriate to user purpose (such as constrained type sets as determined by experts and/or authorities regarding different Core purpose or Core Focus specifications, and/or the like). The foregoing helps ensure the reliability and responsive of PERCos processes and results as relates to user CPEs, including the reliability and responsiveness of PERCos, identification, filtering, evaluation, prioritization, and/or selections processes. Such reliability, and in some embodiments, for example, supported by some PERCos embodiments as selectable of trust assurance levels (e.g. 1-5 or the like) regarding EF testing and Cred quality helps insure that the Stakeholder involved in supplying knowledge and/or experience assisting users in identifying, evaluating, and/or selecting one or more resources is sufficiently reliable for the current active purpose, such as providing a user set and a PERCos (or like) arrangement with sufficient information to enable them to, and/or have others provide, as in the cat behavior example herein, sufficient expert information regarding diagnosing and/or treating of the user set's cat so as to have an optimum Outcome regarding rectifying the cat's behavioral problem.
In another PERCos example that can, for example, be supported in some embodiments, a user may decide to initiate a relationship set where a small group of approximately a dozen users may get together to discuss near-term planet/human ecological issues focusing initially on threatened species, circumstances related to such wildlife species status, and what generally member individuals collectively and individually may be able to do help preserve certain species.
PERCos embodiments, might, for example, be used in differing ways to establish such a group.
For example, the initiating user ("IU") could define differing characteristics that may provide synergistic, complementary contributors to the group function. For example, the IU may wish to have several individuals as members who have at least MS degrees in the academic area of Wildlife Science, Wildlife Management, Environmental Science, and/or the like.
Further, the IU
may wish these individuals to have good communication skills. Further, the IU
wants such individuals, to have a particular interest in understanding and working towards the preservation of threatened mammal species. The IU further wants several individuals who are skilled, accomplished, and financially substantial business men and women, who have the same interests as above, and have a minimum bachelor's degree from an accredited college, but no requirement that the degree be in an ecological management or science area. Lastly, the IU
wants several individuals who have a minimum bachelor's degree, and substantial experience and success in working with one or more non-profit groups and achieving notable success. The IU may specify a CPE for examining specific and/or general cosmos PERCos participant resources stores using specification criteria stipulated herein.
In another example supported in some embodiments, a user set decides to initiate a small movie co-viewing club comprised of approximately 20 individuals where the focus is collaborative researching, identifying, selecting, co-attending, discussion and co-blogging about adventure movies and dramas. The group is intended to function as a collective intelligence/knowledge, evaluation, experiencing, and publishing (blogs) movie club.
In another example supported in some embodiments, a researcher decides to put-together a collective research discussion, analysis, and mutual assistance group focusing on synthetic biology as relates to human liver regenesis and/or replacement.
To provide users with evaluative and purpose-directed resource identification, understanding, prioritization, and utilization in the face of boundless varieties and opportunities of Big Resource, PERCos can support a PERCos cosmos, which is an at least in part administered space comprising a set of resource objects (and may further include resource portions) and related PERCos information management systems. A PERCos cosmos may be further organized according to a set of purpose characterizing, simplification structures, called Dimensions and any associated Facets. Each Dimension and Facet comprises a set of values, which in some cases, may be ordered.
In one or more PERCos embodiments Master Dimensions and/or their associated Facets can be used to generate subspaces of a PERCos cosmos, each of which can have its own set of structures as well as the structures it inherits from its parent space.
For example, Dimension subspaces can be defined by using one or more Facets Dimensions.
Each cosmos subspace, being a space, can also have its own Dimensions. For example, a Master Dimension subspace may have further standardized and interoperable information sets, such as for example, Core Purpose characteristics, user characteristics, resource characteristics, Reputes, and/or the like.
Just as a nautical chart has dimensions, such as depths, heights, coordinates, and/or the like, to characterize depths of water, heights of land, and/or the like, PERCos embodiments Dimensions and Facets can be used to characterize resources according to their Dimensional values. For example, in some embodiments, resource Dimensions may characterize resources according to certain concept approximation properties, such as for example, but not limited to, their Complexity (Material and Functional), Integrity, Reliability, Location, Sophistication/Associated Expertise, language, Quality to Purpose, Value to Purpose, Popularity to Purpose, and/or the like. These Dimensions may be complimented by other resource characteristics, such as Role, efficiency, location, budget, time, and other metrics. Dimensions may organize such descriptive characterizations of resources so to assist in their identification, discovery, evaluation, selection, combination, prioritization, provisioning, and/or usage. They may be used to analyze for similarity and related matching, and/or the like.
Like nautical chart dimensions enable users to identify different points of Atlantic Ocean and compare their relative depths and other attributes, PERCos embodiments Dimensions and Facets enable users/Stakeholders and/or PERCos embodiment processes to identify and compare resources according to Dimensional values.
In some embodiments, Master Dimension Facets are particularly useful for specifying purpose class CPEs. Facets support PERCos approximation matching where the standardized and approximating nature of Facets used in user prescriptive purpose expressions can be matched against resource descriptive purpose expressions to identify one or more purpose classes who have member resources supported by information structures which may be subject to further PERCos purpose assessment and/or selection processes. For example, user characteristics as may be expressed using Facets from user Dimensions, may enable PERCos to employ assertions of user sophistication/expertise relative to any Domain and/or purpose class set in identifying/similarity matching/ assessing/prioritizing/selecting/provisioning and/or using resource sets.
In certain embodiments, PERCos embodiment capabilities are meant to be, at least in part, ubiquitously available. In such cases, PERCos embodiments contextual purpose related features can form basal capabilities of a PERCos based operating environment. These embodiments can transform the nature of operating systems by establishing a new form of relationship between users and resources and their possible use, and may fundamentally alter the nature of a broad spectrum of computing activities. In these PERCos embodiments, contextual purpose features can be deeply interwoven with operating system and other operating environment resource management capabilities and services. This can enable users to have uniquely unified, relevant, and purpose-optimized views into session relevant candidate resource sets.
These capabilities are particularly valuable when users are attempting to identify/employ resources outside their personal areas of particular expertise and command, and/or when users are extracting resources from web Big Data/Big Resource arrays.

With current technology, resources are generally segregated as different, separate things. While, for example, tags and/or full text abstracts may be used to indicate attributes of possible resource items, and clustering, semantic search information, and classification ontologies give certain user fields of view into resource subsets, there is no unified system, in particular Big Data system, that treats resources as atomic elements that are operatively responsive, as one or more resource sets, to at least substantially standardized, contextualized situation/instance-specific user purpose specifications. PERCos's unified system contextual purpose based view into candidate resource sets -- complemented by certain key inventive PERCos attributes and attribute combinations, e.g. without limitation Repute, purpose class and other neighborhood ontology and taxonomic groupings and Domains, standardized purpose contextual Dimensions and Facets, and aggregate common purpose computing resolving such as performed by Coherence services -- optimizes the efficiency and purpose appropriateness of a user's insight into resource and resource portion availability. It further optimizes resource provisioning and usage management through PERCos user purpose/resource expressions and resource and resource portion organization, matching, filtering, prioritization, cohering, combination, provisioning, and usage management. As a result of these capabilities, PERCos can transform and expand the disordered array of Big Data into a component area of Big Resource, comprised of ordered, purpose systematized, user current purpose responsive, component sets of PERCos operating environment arrangements.
PERCos in some embodiments supports a triality of (a) users, (b) resource value chain members, and (c) Repute asserters and fact declarers, the foregoing declaring their respective, operatively intersecting Contextual Purpose Expressions -- which CPEs are in such embodiments comprised of at minimum, a duality of verbs (and/or inferred verbs) and categories, and which expression arrangement support a powerful triality of verbs, categories, and other contextual Dimension information, including, for example, Facet simplifications/approximations.
This can provide an effective purpose process resource framing and user cross-edge approximation computing capability set. For example, PERCos employs in some embodiments, at least in part user purpose specification standardized and interoperable Core Purpose approximation simplification and other approximation capabilities, further standardized approximation Dimensions and Facets, purpose class memberships and applications, resource relational neighborhoods, Repute evaluation/filtering/and prioritization, and common purpose computing Coherence resolution, provisioning, and usage management. These capabilities can be complemented by cross Edge user/computing arrangement dialogue capabilities for purpose expression --including resource selection -- and/or resource utilization for session specific purpose fulfillment such as user purpose related knowledge enhancement and/or experience unfolding, including initiating and/or interim and/or Outcome purpose processes. This dialog can take the form of use of, for example, proffered resource instances and/or session specific resource Frameworks that provide user/computing arrangement purpose fulfillment scaffolding in the form of specific to purpose arrangement of resources, explicitly, by Role, and/or the like, and, for example, provisioned as a user purpose fulfillment environment set.
Through, at least in part, the standardized purpose expressions of the triality of users, resource value chain members, and Cred asserters, PERCos parties, combined , for example, a duality or triality of purpose expressions, enables far more effective and informed presentation of candidate purpose fulfillment arrangements compared with current technologies, particularly when drawing results from web based Big Data, or PERCos Big Resource or when involving resource instances that belong to domains with which users have limited or uneven expertise, that is having a limited capacity to point at (search and retrieve) truly optimal resource sets.
PERCos, as such, provides unique, practical Big Data management and resource utilization solutions ¨ though in some embodiments extended beyond Big Data to Big Resource ¨ for example, as when using PERCos resource to provide purpose related computing environments, such as when using Frameworks involving disparately published, complementary resources, such as people, services, applications, information sets, devices, and the like.

Using user prescriptive interoperable Contextual Purpose Expressions as specifications to be matched against published resource descriptive Contextual Purpose Expression specifications (both direct CPE specifications for resources and referential Repute assertion, Effective Fact, and Faith Fact CPE specifications), PERCos can transform the nature of user relationships with Big Data as well as enlarging it to relationships with Big Resource, fundamentally altering the productivity of resource usage under many circumstances.
PERCos purpose matching with resources occurs directly and/or through intermediate use of one or more PERCos Purpose class ontologies and/or other information organizations. With PERCos, users relate to Big Resource by framing their needs in simple to more descriptive prescriptive purpose compositions, followed (as appropriate) by unfolding cross user/computing arrangement dialogs that orient Big Data and other Big Resource resource inspection through the relating of commonality of purpose (and optionally, other context/descriptive information, related to one or more users (and/or user group(s)). This integration changes the relationship between users and candidate computing arrangement resources. In some embodiments, PERCos supports the assessment and deployment of a new, much broader and more flexible concept of the nature of, and user relationship with, computing related resources, by organizing large, distributed and highly diverse data, services, software, participants, and/or physical resources into functional purpose fulfilling groups.
By providing means to optimally match potential resources to current user purposes, that is the one or more purposes contemporaneous with a current computing arrangement session, computing environments will enable users to acquire, and/or shape, computing resources so as to specifically reflect and support their user purpose fulfillment. Rather than a user having, for example, nebulous relationships with possible resources, where resources are returned in response to key words rather in response to the actual, intended purpose of the resource set use, candidate resources are evaluated as to their capacity to optimally satisfy a user learning, discovery, and/or experience process set, that is the returned resources are considered a domain of user activity rather than an explicit one or more items to be retrieved. As a result, the nature of the user relationships to potential resources, including the full spectrum of resources that could be practically employed, may be fundamentally altered and improved, in particular when the user is not specifically pointing to, that is, specifically requesting/identifying, an explicit one or more particular resources, or if so performing a search and retrieval, when the user's request is insufficiently informed to best fulfill the user's underlying purpose(s).
Through tools that employ contextual purpose standardized and interoperable expressions, including for example purpose related resource set identification, filtering, selection, combination, prioritization, provisioning, and/or usage process management, user resource assessment and user/resource interaction can be inherently influenced, that is directed or otherwise at least in part guided, by such purpose expressions, which may be further combined with related contextual input as well as with user history and crowd behavior and related data and/or events.
With PERCos, resources can represent more than data that is executable by a computing system in the form of applications and/or associated information. In some embodiments, PERCos resources and PERCos operating systems and other environments represent a highly flexible, considerably broadened notion of resource management, identification, evaluation, and utilization where resources may ¨ but are not required to ¨ comprise the entire universe of possible, processable information types, including information that stands for, that is acts as descriptive, interface, and/or control proxies for resource items that reside in the physical world, including, for example, other people, and including interface control information for physical devices that can be directly or indirectly at least in part controlled by users through PERCos purpose fulfillment influenced or controlled processes.

In fact, through PERCos, as in everyday life, purpose fulfillment and resources are ultimately, frequently inseparable in the human mind. Following this principle, users, rather than being contained within silo configurations of current task execution applications and cloud services such as Word, PowerPoint, Google, Yahoo, Wikipedia, or Acrobat -- can characterize their dynamic purpose (that is their current purpose) with an expectation that responsive resource sets in any reasonable combination, for example published as sets, will be identified, filtered, evaluated, selected, prioritized, combined, provisioned, otherwise organized, and/or used, in a manner responsive to satisfying user purpose(s), that is helping users determine and/or computing arrangements calculate "best" available resources as individual items, or as sets, for example in the form of purpose class application environments. PERCos, in some embodiments, can present an at least in part digital environment for user specific purpose quest unfolding and/or enhancement and/or fulfillment. PERCos, in some embodiments, can function, for example, as a portal to any and all PERCos compliant and/or otherwise interpretable resources, including PERCos resource items that have operatively (that is sufficiently or fully) unique one or more identities and associated one or more purpose expressions, purpose classes, and/or other meta data including broader context data use/purpose pertinent information.
Some important PERCos methods sets supporting PERCos exploration and/or discovery, for purpose refinement, and/or unfolding resource exploration, are for example, associated respectively with one or more of: purpose resource publishing, certification, authentication, other integrity processes, Repute purpose value rating, and purpose expression including other meta data specification, including, for example, purpose class specification, governance value chain features (subscription, advertising, societal and other Stakeholder governance, other rights management associated with prescriptive and/or descriptive purpose(s)) and/or PERCos resource instances), and/or the like. These PERCos capabilities provide specification instances supporting, for example, purpose matching/identifying, filtering, selecting, prioritizing, combining, cohering, and/or the like, of multi-party purpose attributes/requirements ¨ both user and Stakeholder, and form key capabilities in the formation, and evolving, at least in part in some embodiments, of self-organization of a purpose cosmos comprising a PERCos web arrangement.
For example, PERCos embodiment compliant resource sets, may, so long as such sets are cohereable where there are combinations, be activated, and further controlled over time, in a manner responsive to applicable, cohered, purpose expressions functioning as a common purpose set of operations, for further example, as such purpose expressions may represent an evolving sequence of unfolding user knowledge enhancement, discovery, experience processes, and/or results observation (whether direct or indirect).
In some PERCos embodiments, there may be several kinds of expressions that may be combined (along with any relevant other contextual, relevant information such as metadata) to provide a composite expression of user purpose. These may include for example:
Common Purpose Expressions = Instances of one or more users and any germane Stakeholder standardized and interoperable and other interpretable sets of purpose and related specifications (for example purpose expressions) which are amalgamated to form a resolved (including when applicable, arbitrated or otherwise determined) consolidation of the specified and/or inferred, interests and/or priorities and/or requirements, of all relevant specifying parties related to resource identification, evaluation, provisioning, usage, consequences, and/or the like for respective purpose satisfaction agreement of such parties.

Common Purpose Sharing = One or more users with certain purposes that may be commonly served by mutual participation and shared interest as regards to one or more PERCos sessions exchange or otherwise have supplied their purpose expressions and any germane other related specifications, and where the foregoing is resolved into provisioned or published operating specifications for shared PERCos activity. Such shared activity involves sharing to common and/or complementary objectives through the use of one or more resource sets.
And any combinations of the foregoing.
In some embodiments, during any of the foregoing operations, one or more new resources (including for example specifications) may be created, through for example one or more instruction based processes, including for example instruction sets resulting from the use of purpose class applications, where user PERCos purposeful activity portions, extracted information, and/or derived information may be combined with any instruction set arrangement, with the results published, or otherwise retained, as a PERCos resource, which may be associated with purpose expression, purpose class, resource and/or resource class (including for example any participant and/or participant class), Domain/category class, external to PERCos one or more classes, affinity groups, crowd groups, and/or the like.
Some PERCos embodiments may include sets of intelligent tools for purpose operations which may, for example, include:

= Tools for, and/or assisting users in, the initial formulation and/or enhancement of purpose expressions = Tools for resource organization responsive to purpose, including tools reflective of expertise, for example, tools supporting the creation, editing, and/or modification of purpose class and/or purpose based resource (including, for example, participant) ontologies and/or taxonomies (including, for example, participant ontologies and the like), and, for example may also or alternatively include one or more of, tools establishing and/or assisting in identifying and/or employing relationships among resource sets and/or portions and/or resource classes and/or purpose classes and/or purpose expression sets = Tools and/or other capabilities (embeddable technologies) for optimal framing of purpose expressions resulting from expertise-framed interface contexts -- such as the use of faceting interfaces and/or purpose organized resource and/or other knowledge related graphing, including clustering, tools supporting resource selection = Tools for managing massive resource sets where perspective dimensions, such as those graphed using Dimension Facets sets, are organized as conceptual simplifications and perspectives in a manner optimally structured to support expertise-framed contexts, including, for example, representations of spaces resulting from combination of certain or all specified Dimension Facets, which may be complemented by other meta-data specifications and where the foregoing may be manipulated, for example, by altering Facet values and/or selections, for evaluation of alternative results, and/or the like = Tools for preferences and/or other profile Specifications, in general and/or as specifically associated with one or more purpose classes, participant classes, Domain classes, resource classes, resource neighborhoods, and/or the like, where such preferences and/or other profile information are cohered with the current user one or more CPEs and/or Purpose Statements and/or Foundations and/or intended Frameworks (including, for example, purpose class applications), for example, as respectively associated with specific purpose class sets, to influence and/or control the identification and/or selection of resources and/or the preparation of session operating specifications = Tools for the manipulation and/or editing of purpose class applications, Frameworks, user and/or computing arrangement Foundations, and/or the like = Tools for publishing and/or administering resources, PERCos cosmos and/or Domain registration and ontological and/or taxonomic associations, identification formulation, purpose value chain management, for both user set and other group purpose administration, and/or the like = Tools and related infrastructure for purpose network managing, including purpose related caching, by for example, storing frequently used purpose related associations, and/or resources, as described herein, so as to improve network operating efficiency and/or reliability and/or security, where such information, for example, may be maintained at various network caching locations in general and/or as may be desirable locally and/or regionally as a result of differing purpose related usage patterns and/or as specified by network manager sets = Tools for users, Participants, and/or resource integrity supervision, administration, and/or enforcement, including associating differing security policies/levels/requirements with one or more or differing purpose classes, resource classes, Participant classes, PERCos computing arrangements (and/or classes thereof), and/or one or more affinity groups and/or affinity group classes = Tools for resource related specification for navigation and inspection, for example, tools assisting users in the inspection and evaluation of candidate resources through, for example, relational database manipulation/filtering/weighting of purpose related attributes such as Master Dimension Facets and/or auxiliary Dimensions information to view responsive resource lists, which may be ranked and/or displayed with at least a portion of such attribute conditions and/or with non-specified attributes = Tools for purpose language specification, annotation (to, for example, assist programmers and/or user's in use of language elements) and/or tools for associating symbolization with Constructs, such as with one or more purpose class applications, other Frameworks, Foundations, CPEs, affinity groups, Participants and/or Participant classes, purpose classes, and/or Domains/categories, and where such tools may be used by users, standards groups, purpose environment utilities, affinity groups, governments, and/or the like = Tools for managing stored "active" and/or historical sessions and/or session information, whether user specific, affinity group, and/or crowd behavior class or other grouping and supporting further cross-edge unfolding of user purpose and/or results evolution through filtering, prioritizing, and/or presenting information based, for example, on Dimension Facets, including, for example, Repute Dimension Facets such as Quality to Purpose, Value to Purpose, Value Contributing to Purpose, and/or the like, and/or user Dimension Facets such as user sophistication as related to purpose or purpose class, and/or other Dimension and/or metadata and/or the like = Tools for the creating, editing/manipulating, and/or managing of Constructs and related resources, including, for example, Frameworks, Foundations, resonances, participants, and/or other resources for users and Stakeholders, including tools for associating such items with purpose expressions and/or resources, for example, through association with one or more CPEs and/or purpose classes, participants and/or Participant classes, resource or resource classes, Domain categories and/or other groupings, and/or the like Human purpose expressed across the Edge can take the form of an unfolding process where user output to computer (computer input) and output from computer to user (input to user) are dynamically interlinked and encompass a cross-time dialog and/or set of observations, an interactive flow of input involving both users and their PERCos computing arrangements (and any PERCos and/or otherwise complementary services) functioning as session interacting "actors." For Example, such interactions may occur during purpose unfolding for purpose fulfillment, including purpose related learning, exploration, discovery, and/or event and/or user observed based interim results.

These cross-Edge interactions may span one or more sessions, that is the user/computer arrangement PERCos dialog may be paused/interrupted, and may be continued at a later time and/or at different PERCos node one or more locations.
Within such PERCos sessions, computer domain operations may include computer side PERCos supported processes that, based on historical user information, expert system operations, and/or artificial intelligence and/or the like, at least in part anticipate user/computer priorities as may be associated with user(s), purpose(s) and/or may include support for user/system interactions complemented by, and initiated at least in part by, artificial intelligence interpretation of user purpose related actions such as CPE specification and/or purpose class application user interface input, and where such Al and/or the like processes may further interpret information regarding user stored profile (including, for example, preferences) and/or historical use in general and/or as associated with one or more purpose classes and/or user specified CPE, as well as input related to one or more purpose classes and/or CPE set and/or in general derived from crowd, participant class, affinity group, profile and/or preferences, and/or other like input.
In some PERCos embodiments, one or more resources may assist purpose operations through recognition of informational, sequential, and/or temporal patterns involving user and/or user group input(s), and/or reading and interpreting user and/or at least an additional portion of a user group biometric information such as facial expressions, breathing patterns, voice amplitude, cadence, and/or frequency information, orientation and/or other physical positioning information between/among session participants and/or visual and/or other recognition of objects in a user computing arrangement and/or at least a portion of any change to such computing environment.
Such information may also include provision of notices, reminders and/or other information in advance of one or more deadlines and/or other sequential and/or temporal events.

In some embodiments, a shared purpose expression is a specification of purpose agreed to by a group of users. shared purpose expressions may be used in one or more shared purpose sessions (for example including the session in which the shared purpose expression was created and maintained), they may be published for later use by said same group, and/or they be publicly published for use by one or more specified affinity groups, participant classes, associated with and/or as a member of a purpose class set, and/or the like, shared purpose expressions may be created by one or more parties and then published to an affinity group set, participant class set, or universally, whereby it may attract other prospective users to shared purpose, common purpose computing session, or to a shared purpose distributed/aggregate session set where parties participate in such PERCos sessions (or parts thereof) independent of some or all other participants, but where one or more aspects, including for example results, are at least in part shared and comprise a shared Outcome, optionally with shared interim results.
Shared purpose expressions may occur in a shared PERCos session set as shared purpose expression portion sets that specify differing roles for each participant set. Such shared purpose expressions and any associated shared purpose expression portion sets, may be memorialized at least in part in a legal agreement set that may stipulate sharing rights of participants sets to Outcome and/or interim results, including financial compensation for time invested, resources contributes, or the like, in respective participant/User set work related to such Outcome and/or interim results, creation rights, publishing rights, and/or value of at least certain aspects of Outcome produced.
In some embodiments, PERCos shared purpose sessions may comprise resources and users with standardized, interoperable purpose expressions which are resolved so that users may learn about and/or discover resource sets and/or resource portion sets and interact with other users having the same or sufficiently similar (by specification) shared purpose, and/or interact with other users and/or Stakeholders having an interest in such resulting resource and/or resource portion set. Because of users' varying contexts, and/or because of the approximation computing nature of user CPEs and the secondary differences that may exist between users employing the same CPE, different user sets results sets may differ leading to differing user experiences and/or other Outcomes.

In some embodiments, PERCos enables groups of users to declare and/or discover shared purposes. For example, a user may wish to declare their interest in a purpose, for example, fishing, home digital audio distribution, cooking Cajun food, and/or the like, and wish to interact in some fashion with other participants, perhaps unknown to an IU, regarding this common purpose, such as viewing and commenting on a movie together, sharing music with one or more people, and/or the like. For example, someone who has more expertise than the IU may be a desirable PERCos session companion (for example, along with using, for example, purpose class application tools supporting such sharing, for example, simulcast video and audio conferencing, texting, chatting, and the like). This may include, for example, identifying someone to help an IU set with a task such as a chemistry experiment, collective writing of one or more blog articles, replacing a hard drive in a notebook computer, singing in a music chorus, and/or playing in a band with the participants physically distant but sharing a common purpose computing session, and/or the like.
In some embodiments, shared purpose sessions may be interactive, for example with users interacting with at least a portion of the same resources associated with shared purpose expressions for the session. In some embodiments, this may involve one or more publishers who have published resources for shared purpose sessions (individually and/or in groups). Users may elect to create resources that are specifically for one or more shared purposes and thereby act as publishers. Shared purpose class applications may be published as environments for users/participants to pursue shared purposes.
For example, in some PERCos embodiments, one aspect of shared purpose is social interactions and potential bonding through expressions of shared purpose and/or through sharing experiences during a common purpose computing activity. One or more users may dynamically undertake purpose operations within, for example, a shared purpose session, and may be subject to other user set preferences, for example, regarding interactions with other users and/or resources. Such dynamic activity may spawn event messages to other candidate one or more session users (and/or automatically provision a user set) and/or users, individually or collectively through, for example polling, may decide to share at least a portion of their unfolding experiences in the form of a user set joining an in progress PERCos session, and/or recording, for example, and publishing as a resource, for a further user set session activity and/or results and providing such information to a user set. In such an example, as with earlier examples in this section, users may benefit not only from those resources associated with a purpose class and/or being sufficiently similarity matched with a user Purpose Statement and/or CPE, which, for example, might be augmented by other contextual information such as shared (and/or complementary) preferences, profiles, PERCos history information, and the like, but additionally benefit from other users' and/or Participants perspective, interactions, commentary and/or narrative associated with operations within that shared purpose session.
During and after such operations one or more users may establish relationships with other users, such as for example forming bonds associated with one or more purpose classes, resource classes (for example, participant classes), which may lead to further common benefit, social integration, and/or purpose satisfaction/fulfillment. For example, in some embodiments, one or more users may wish to create an affinity group, such as, for example, a modern jazz appreciation group comprised of individuals who have moderate experience with modern jazz and enjoy it greatly and, who have graduate degrees in sociology or also enjoy Cajun cooking, and such participants, as users, may use PERCos Repute tools, PERCos identified other resources, and each other, to collaboratively, collectively help learn about and discover Modem Jazz and Cajun cooking, infused with an understanding and/or study of, for example, related sociology theory and related culture, such as cultural background for Jazz in Louisiana. In some embodiments, affinity groups may be based on shared purpose expressions such as shared purpose classes which may involve synergy complementary elements, forming potentially complex relationships of users and/or groups with resources -- including participants who may become involved as users -- the foregoing which may be associated with an expressed shared purpose specification set.
PERCos purpose expressions specification arrangements in different embodiments may take differing forms. Consistent among these embodiments are the principles of simplification of expression, where such expression may take the form of an approximation of such user purpose to facilitate efficiency of processes and the learning, experiencing, and/or discovery processes that may unfold responsive to such expression specifications.
PERCos operating environment/system may provide for the specification (and/or inferring) of verb and category sets, which may be interpreted in combination as Core Purpose Expressions.
Some of these embodiments may support the use of certain grammatical, clarifying elements such as prepositions and adverbs (particularly as constrained in variety as logically applicable to specific Core Purpose or other CPE sets), and may further support the specification of additional clarifying elements, including various situational and other contextual characteristics, such as in the form of other Master Dimension Facets and/or auxiliary Dimensions and/or the like. For simplicity of operation as well as standardization/interoperability management, options available in each grouping of characteristics or characteristic/subcharacteristics may be in constrained to limited list option sets, where such limited set of characteristic options facilitates ease of choice by users of logical and/or frequently applicable choices for purpose approximation representations and/or metadata matching. In some embodiments, synonym sets associated with specific such constrained list members may be user viewable for some or all of such members to inform user understanding and/or guide user characteristic selection for PERCos purpose expression, and/or usage of any of such synonyms may be automatically or with user approval, translated to the operative synonym terminology.

PERCos embodiments may employ differing expression approximation simplification schemas.
For example, PERCos embodiments may provide for the separate specification of verbs and Domain categories (where categories, for example, may be organized in a manner comparable to DMOZ categorization hierarchical arrangement). Such embodiments might, for example, first, or simultaneously with category selection, present a faceting verb selection interface (or vice versa a Domain category faceting selection interface then a verb faceting interface). In such embodiments, for example, a user might select one or more categories and/or subcategories from an unrestricted, or restricted to logically consistent/appropriate, choice set. After completing such verb and Domain category selection, with or without additional selection or other entry of prepositions, adverbs, and/or the like, in such embodiments, the user would have specified a Core Purpose set employing standardized, interoperably interpretable expression elements and combinations and representing a Purpose approximation.
In PERCos embodiments, various Core Purpose supplementing approaches can be adopted where such approaches employ similar but differing purpose expression concept simplification schemas.
In one embodiment set, for example, Core Purposes are supplemented with other principle simplification characterizations provided through a Master Dimension/Facet arrangement, which may be further or alternatively use an auxiliary Dimension approach. In this embodiment set, Master Dimensions are comprised of standardized characterizations complementing Core Purposes (which can also be defined, for example, as Master Dimension characterizations).
These further Master Dimensions are grouped in principal, logical simplification, vector characterizing groupings.

Master Dimensions are comprised of Facets and any associated specified values.
In some embodiments, these Core Purpose logically complementing Master Dimension groupings may be comprised of, for example, the categories of users; resources; Reputes knowledge/expertise/opinions assertions and Effective and Faith Facts regarding resources; and special Facets (e.g. icons and/or other symbolic or short-hand notions representing any Master Dimension and associated values expression set). Such Master Dimension Core Purpose and Dimension Facets are used to express purpose approximation components that, when combined with Core Purpose specifications, can be used for identifying, evaluating, determining, prioritizing, combining, and/or provisioning resource instances and/or neighborhoods and/or their members, such as, for example, identifying and provisioning for user inspection, for example through similarity matching and prioritizing, most relevant one or more purpose classes, resource members sets, and/or resource instances (when not calculated after determination of class, neighborhood, or other grouping membership).
Supplementing these types of Master Dimension approximation embodiments, further or alternative specification in some embodiments may be made in support of further identification, evaluation, determination, prioritization, combination, and/or provisionment of class member resources and/or resource portions of resource neighborhoods, such as purpose classes sets, identified, for example, through use of Master Dimensions and Facets. In this embodiment or use case set, users and Stakeholders may specify auxiliary Dimensions.
Auxiliary Dimension represent interpretable specifications which are not based primarily on standardized, interoperable lists of component elements used in defining purpose approximation neighborhoods, but which groupings may each represent open arrangements of interpretable element sets that may, for example, be used in similarity matching and filtering of purpose class or other neighborhood members and/or portions thereof. Auxiliary Dimension open specification instances may be inefficient and/or inappropriately specific when applied, under certain circumstances, for example, to identifying and/or evaluating items within Big Resource or Big Data to determine candidate groupings of resources, but auxiliary Dimensions may provide purpose specifications that are more appropriate under some embodiments or circumstances when applied to purpose approximation class or other group member sets to resolve in accordance with more specific user or Stakeholder specified criteria to specific resource instance results. Such auxiliary Dimensions of open specification arrangements of interpretable elements are organized in some embodiments in logical groupings and may be further organized with certain simplification subsets, the foregoing for assisting users and Stakeholders in understanding, selecting, and/or organizing such criteria representing contextual and process optimizing user and Stakeholder selecting/filtering/evaluating parameters.
Auxiliary Dimensions may be, in some embodiments, arranged in user logical understanding simplification groupings, such as for:
1. process specifications for:
a. affinity, societal, and/or commercial and/or the like instructions, such as rights and/or obligations rules governance specifications, and which may include, for example, related event based triggers, controls, and process flow management;
b. resonance specifications, which are instructions sets associated with at least one purpose expression, and which can specify condition sets under which such conditions presence and/or absence (individually, in subsets, and/or as a whole) may facilitate and/or detract from, as specified, user purpose fulfillment optimization, and which may include synergy instructions regarding complementary contributing resources sets;
c. process automation instructions that provide, and/or provide control information for, for example, software, services, and/or hardware instructions that may facilitate identifying, processing, and/or filtering based upon such instructions in order to optimize user purpose fulfillment results, and which may include, related, event based triggers, controls, and process flow management.

2. general data items, such as, for example, information stored in profiles, preferences, user PERCos usage history stores, and/or as generally published "crowd" usage history related information such as inferred crowd preferences and history information as related to purpose, resource, and/or other useful classes and/or instances.
3. PERCos Constructs such as information arrangement employed as purpose related session building and/or evaluation blocks such as Frameworks, Foundations, and/or the like.
4. Free form parameterization such as Boolean expressions, metadata lists (e.g. tags, structured information arrangements), and/or the like.
In some PERCos embodiments, CPE specification interfaces may employ supplementing and/or alternative Master Dimensions arranged as groupings of controlled vocabulary choices where such Dimension groupings directly contain alternative user choices, versus representing Master Facet types (Core Purpose, user, resource, Repute, special symbol). For example, some embodiments in such expression simplification arrangements may provide controlled vocabulary instances representing choices available under certain specific Dimension types, such as, for example some set of data characteristics; Roles; relationships among or between; tests and routines; resource items; quality of experience; modalities; and/or the like.
One or more of these choice sets may itself have its options organized by class and/or other category structures to enable easier user navigation and choice if the choice set is sufficiently large. These choice sets may be organized in a manner comparable, for example, to the organization management that may be applied to Domain category choices. As with some other embodiments of PERCos, these embodiments may use user faceting interfaces to allow choices, based upon prior specification elements and/or user and/or crowd behavior patterns/history where faceting choices in any given selection column may be constrained by that set which is logically sensible and/or significantly likely as, for example, selected by one or more general and/or Domain expert and/or authority sets. Such a user interface can allow, as also may be supported in with choices within some Master Dimension embodiments, the toggle selection between a logically constrained set of choices derived as a subset of the full constrained vocabulary list for a given Dimension, and the full constrained or alternatively constrained vocabulary to allow users and Stakeholders to alter the logically available choices in other one or more Dimensions so as to evaluate the impact on user choices and to, for example, allow user choice between simple, versus more choice selection variety, such as choice between simple, moderate, and extended faceting list choice complexity arrangements. Custom constrained vocabulary sets may be specified by Participant sets, including, for example, affinity group sets.
Such alternative controlled vocabulary arrangements may also, in some embodiments, be used for portions, or in some embodiments for all, for example, of auxiliary Dimensions user purpose expression specification interfaces.
Such a more elaborated category oriented design might be used in arrangements, for example, having fairly extensive choice selections under some or all of the Dimension category types, and can offer a differing perspective on user simplification specification sets for purpose approximation. This kind of arrangement may provide for more extensive, standardized resource characterization flexibility and may, under some circumstances, be more responsive and efficient for users than embodiments using free form parameterization to identify specific, purpose responsive resources, though these embodiments may be less effective in characterizing purpose approximation for identifying purpose neighborhoods. These embodiments may have, for certain examples, usefulness in arrangements, or circumstances, where direct similarity is evaluated against resource instances, but given quality of experience, modalities, and/or certain other variables, may be less efficient and beneficial in use for similarity matching with purpose approximation sets such as purpose classes.
In another PERCos embodiment set, CPE specification may employ Core Purpose specification through the use of standardized, constrained lists of verbs characterizing an intent perspective regarding activity type, and category arrangements, for example structured in a manner comparable, or otherwise similar to, DMOZ. In this embodiment set, Master Dimension simplifications might be organized as verbs, categories, characteristics, focus, perspectives, tests, and Reputes. Other, further Master Dimensions might be employed representing "interactions" and/or "governance and rules" given the importance of interactive relationships and processes in the emerging connected world (or this Dimension might be a part of, for example, "perspectives") and given the importance of automating processes and enforcing governmental/societal/affinity group rules and results/consequences (or this Dimension might be part of, for example, "characteristics"). As with the other described embodiment examples, these Dimensions are meant to comprise a logical groupings set that users can readily relate to as conceptually related organizational purpose specification simplification arrangements and where such Dimension choice structures, in some embodiments, are comprised of constrained sets of options to ensure reasonable simplicity of operation and where such constrained sets may, at any given point in a sequence set, be limited to a number of logically related choices, including, for example, limited value selections, as determined by general and/or Domain experts and/or authority sets and to be appropriate for simplification, approximation, and/or efficiency reasons.
In some PERCos embodiments the notion of Concept Description Schema (CDS) is employed through, in part, the use of Dimension, Facets, and their instances and any associated values.
CDSs are multi-dimensional spaces used for organizing concepts, for representing their similarities, differences, clustering, graphing, nearness analysis, and otherwise for providing elements for communications and evaluation. Its primary role is providing expression elements for PERCos environment participants to articulate purpose orientation characterizations ¨ CPEs -- for framing the foundation for a PERCos session and for making associations with resources that can contribute to PERCos sessions interim results and/or Outcomes. These structures support the identification, evaluation, prioritization (as used herein including, for example, ranking), selection, combination, and/or provisioning of resource sets and/or portions thereof, and associated user purpose orientations through the matching analysis and/or other association of CPEs (framing purpose expressions and/or Purpose Statements) with resource sets. All of this may involve generated, constructed, and/or identified elements matching and/or contributing to an appropriate user purpose fulfillment process, including, for example, CDS facilitated information retrieval, unfolding multi-media entertainment, business productivity purpose class applications and other Frameworks, human interaction contexts, and/or the like.
Both for intellectual control, logical relational processing, and for implementation efficiency, in some embodiments, CDSs may be grouped into Dimensions (as with Master Dimensions described herein), which in certain embodiments may consist of a cluster of Facets that are conceptually more closely related to each other than to other Facets; in some embodiments, Facets may themselves be further structured into subfacets (and subsub Facets ...).
The specific structures described herein represent logical, and in some instances, compelling simplifications for purpose approximation. They facilitate functional and/or purpose optimization (of both users and Stakeholders); while these structures are not specifically, uniquely determined by the structure of the universe, by the natural language used, or by the way the human brain works, they are informed to one or another degree by each of these considerations, and normally are particularly informed by the nature of modem human behavioral and conceptual proclivities. In particular, the number of levels of subdomains within a domain involves two trade-offs: breadth vs. depth (more terms per level vs.
more levels) and generality vs. specificity (a few broad classifications vs. many very specific ones).
There is significant correlation between terms employed by Facets in the exemplary Dimensions, and PERCos uses of grammatical parts of speech (in English): verbs and verb equivalents (as well as inferred verbs) typically involve verbs or verb like phrases or comparable actions; categories, nouns or noun phrases; characteristics, focuses, and perspectives, may, in some embodiments, employ adverbs, adjectives, and/or adjective-like constructions; tests, verbs or verb phrases; Reputes, standardized PERCos qualitative representations and associated information. However, this is a matter of choice, as Master Dimensions employ verbs, categories, users, resources, Reputes, and symbols, and other embodiments may employ other simplification strategies.
For purpose approximation, in some embodiments, most of the benefit to a user from a specification standpoint comes from relatively coarse, approximating classifications, rather than highly-detailed schemes developed for information professionals, such as the Library of Congress Classifications, though certain CDS implementations, particularly certain use focused implementations, may have further levels of sub-domains.
The simplification groupings and other features of these embodiments may be in part or whole combined, that is their purpose simplification Dimensions and any associated features may be employed, as perspective specification tools, in any desired combination, using the same, or operatively similar, conceptual groupings.
In some PERCos embodiments there are one or more languages for purpose expressions. For efficiency and/or interoperability, such languages may have formal syntax and semantics and be supported by associated resources, tools and/or supporting environments. For example PERCos embodiments Platform Services and environment(s) may provide such support.
Such languages may take the form of:
1. High level, user, Stakeholder, and administrator languages, which may be entirely and/or substantially use symbolic and/or named elements, with or without syntactic Constructs and may employ differing icons as representative of different expression elements, such as, for example differing icons for each respective and/or groups and/or category representatives for standardized verbs, Domains and/or Facets, and/or Constructs, for example, representing one or a group of purpose class applications, Frameworks, Foundations, resonances, Repute classes, purpose classes, CPEs, Purpose Statements and/or the like; and/or 2. Lower level programming environments supporting basic PERCos environment process and internal resource control functions for providing instruction level code and moderate level semantic and syntactic elements, for example, as corresponds to verbs, Domains, Dimensions, Facets, Values, Constructs, Repute classes, resonances, and/or the like, that when specified in a logical manner form computer processing instruction sets.
PERCos compliant computer applications, such as purpose class applications and non-PERCos resource applications employing a PERCos plug-in set and/or employing integrated capabilities made available through, for example, an API, may incorporate purpose language expression and interpretation capabilities for use by one or more users and/or Stakeholders and/or their computing arrangement(s) to specify and/or interpret a purpose expression or statement set in a manner consistent with context, purpose focus, interim results, Outcomes, and/or user experience set associated with the associated underlying purpose application design.
Purpose expression languages may have one or more vocabularies, which for example, may be segmented and/or combined to provide context appropriate purpose expressions and associated vocabularies to users and/or Stakeholders.
Purpose expression languages may include capabilities for interaction of users with "real world"
tangible processes and resources, for example physical transport, autonomous and semi-autonomous machinery, existing and legacy automation systems and/or other real world physical resources such as real world capabilities employed in manufacturing and/or services (e.g.
production line provisioning and/or control, electricity provisioning and/or generation control, water provisioning and/or storage management, temperature control, knowledge/help and/or administration activities, and/or the like), purpose expression languages may include terms that reflect the real world, and provide support in some PERCos embodiments, for example, to interact with real world environments such as communicating with computing arrangements involved in electrical grid transformers and electric transmission systems, enabling real world physical resources to become part of, or be otherwise influenced and/or controlled by, a purposeful system such as found in the form of PERCos embodiments.
In some embodiments, PERCos purpose expressions include Core Purpose Expressions, which comprise verb and category sets. Core Purpose Expression instances support effective, efficient and interoperable interactions of users across the Edge for purpose formulation, resolution, and/or results. Such Core Purpose Expressions can form a first order simplification that represents user objectives sets stated in a simple, high level form, and comprising of one or more verbs representing an action perspective set, and one or more categories representing a subject set. For example, the verb Learn might be combined with the Domain Science/Physics/Astronomical, or Perform Vehicle/Engine/Repair & Maintenance, or Consume Food/Chinese, as high level Outcome purposes, where resources such as corresponding purpose class applications appropriate to these desired purposes may be arrayed for user evaluation, selection, provisioning, and usage, and where such purpose class application interfaces may guide users to satisfying Outcomes, including, for example, specifying Consume Food/Chinese might use the users request and prompt, for example with a faceting engine, for contextual information orienting to a more specific Outcome type such as healthy (e.g.
low fat), whether at home or as a guest or at a restaurant, physical location, price, spiciness, regional type, ambience, parking, hours of operation, length of time in business, and/or Repute variables, and/or the like.
In such instances Core Purpose Expressions may result in a user being presented with purpose class applications, where such one or more applications specialize in supporting, or are flexibly adaptive and can specifically support, the user sets specific Outcome type. A
Core Purpose Expression may be represented by, for example, a standardized symbol that corresponds to its purpose. Purpose class applications may use such a Core Purpose symbol as part of a symbol representing a publisher's or other Stakeholder's specific instance of such an application, assisting the use in making a logical association to a purpose class application a simpler, more intuitive process.
Verbs and verb equivalents may function as key elements in the specification of purpose, since they express intent generalizations that can be associated with "things," such as PERCos Domain categories. In some embodiments verbs may be organized into lexicons to provide users/Stakeholders with means to effectively identify and/or express their purpose approximation. In some embodiments, such lexicons may be significantly limited in quantity to comprise, for example some tens of verbs such as approximately forty, eighty, or one hundred twenty; in some other embodiments, verbs may be limited to hundreds of verbs as a constrained verb vocabulary. This limitation of available verbs may be implemented in support of approximation learning, standardization, interoperability, efficiency of operation, and/or ease of use of user of at least a portion of a PERCos embodiment interface and/or ease of user understanding and/or use of and/or relating to verb specification options.
Such limiting of verb choice variety to, for example, optimize standardization, interoperability, simplification, and/or purpose expression approximation may be presented for specification purposes, for example, as a capability of a faceting interface, whereby for example, a finite list of verbs is presented to a user or user group as a faceting scrollable option list, and for example, where such finite list may be visually expanded by for example cursor movement over a given verb to display a list of its operative synonyms, which such synonym list may form a verb purpose class perspective simplification associated with such given verb. From such a faceting constrained list, for example, a user may, for example, select one or more verbs and associate these, for example, by then using other aspects of such a faceting interface to view Domain category list(s), including any subsequent category refinement lists, for noun selection. Since learning and discovery are often concerned with arriving in resource neighborhood comprising suitable or best practically available resources to support user purposes, constrained verb lists may provide highly effective approximate conceptual perspective positioning when conjoined with Domain category information.
In some embodiments, such sets of verbs may be presented to users and/or Stakeholders in lexicons, such as for example simple, medium, advanced and/or these lexicons may be specific to one or more purpose classes and/or Domains categories and/or resource classes and where such lexicon variety may be a user interface and/or programmatic choice for users and/or Stakeholders. Lexicons may include, for example, automatic scaling, ordering, priority and/or other organizing principles, which may be, for example, resource class sets such as purpose class, Participant class, Domain class, Repute class, resonance class, and/or context specific set associated.
In some embodiments, verb set lexicons may comprise verbs that have associated classes with members comprising other associated verbs, for example verb class "Learn" may comprise members "Understand, Train, Educate, Absorb, Study, Master, Familiarize"
and/or the like, which may comprise purpose approximation simplification conceptual perspective synonyms.
These verb classes may be extensible and/or ordering of verb members may determine priority and/or other metrics. Affinity Groups and standards bodies such as purpose class, Domain class, standards, and/or utility institutions and/or the like, including, for example, Domain society groups (e.g. ACM, IEEE, NSF, and/or the like), for profit corporations (like credentialing and security companies such as Symantec Corporation), or public utilities (such as publically owned electricity utilities), governments, and/or the like, may manage and standardize verb lists for PERCos embodiment purpose approximation and Core Purpose Expression.
In some embodiments, PERCos categories may reference one or more verb lexicons, which for example may comprise verbs constrained by verb-category pairs that are in widespread use. For example verb "Eat" may not be generally associated with category "Motorcycles"
but may be associated with category "Fish". Faceting "intelligent" user interfaces in some embodiments may organize choices as may be appropriate for approximation computing, and for example, a Domain category and any further subcategories may be first selected followed by a constrained list of standardized verbs that are logically appropriate for the category (similar pair associated verb/category lexicons may be employed in embodiments when the system and/or users first identifies a PERCos category set, including for example a Domain category set, and where only logically appropriate one or more verbs from a PERCos verb lexicon are made available for evaluation and/or selection). In some embodiments, there may be an "override"
capability allowing users and/or administrators and/or some other authority to enable the use of an expanded, or unrestricted, verb list and/or direct entry, of one or more verbs by a user, this functioning as a less or unstandardized verb expression capability set that may complement general standardized lexicons, including constrained lists as described. These expanded or unrestricted verb expression capabilities may be less efficient, and have functional limitations from an interoperability standpoint, but when used with well-designed synonym lists, may allow for more natural user expression and may provide adequate matching capability to the classes and/or individual instance sets of resources, purpose expressions, CPEs, Purpose Statements, participants, and/or the like.
In certain embodiments, PERCos verb one or more lexicons are at least in part determined by general knowledge, Domain category, and/or purpose class experts. Such lexicon determinations may supplement a standardized, general, common purpose base lexicon (and/or base expertise level such as a base medium sophistication level for a given purpose class and/or Domain category class set). Such experts may be employed as consultants and/or employees by such affinity group and/or standards groups and/or web service companies as and/or may be contributors to the standards activities and/or knowledge base sets of such groups. Such experts attempt to, given their insight into the nature of use of verbs in their Domain and/or purpose classes, define a constrained, standardized list and/or relational arrangement, which can be used, for example, in support of user and/or Stakeholder Core Purpose Expression and/or other CPE

specification activity in PERCos purpose approximation and approximation related learning for similarity matching and other shared and common purpose computing functions.
In some embodiments, user histories, historical crowd behavior in general, and/or as associated with a PERCos class set, may influence and/or constrain lexicons and/or the ordering of verb alternatives, such that users may be presented with a more effective, constrained and/or ordered verb (and/or respectively, Domain category) selection interface. In some embodiments, instances and/or classes of participants, affinity groups, Stakeholders, societal/governmental groups, and/or the like may create for their own use, for example for parties for which they have a responsibility (such as employees, citizens, members and/or the like) and/or for wider publishing, lexicons that they have modified from a PERCos standard lexicon and/or which they have originated. PERCos standards bodies and/or other governing organizations may constrain who may create lexicons and/or associate rules of governance with any such lexicon so as to have a sufficiently ordered and/or interoperable and/or efficient PERCos cosmos, or set of cosmos purpose, Domain category, participant, broader or differently oriented resource, Repute, and/or the like embodiment classes or other ontological groupings.
In some embodiments, PERCos provides one or more Domain category and/or global category arrangements and/or combinations of the foregoing for purpose specification and operations. In some embodiments, category class structures like those described by DMOZ may be employed, such category organizations being presented to users, for example, by faceting interface arrangements that allow easy access to specific subcategories, such as selecting Science/Physics/Nuclear/Theoretical. Higher order categories may be represented by symbols, for example, where any such icon could be selected to bring an individual to a specification point in a category/subcategory sequence. For example, the symbol for Nuclear might be a small impression of a molecule while baking might show an icon image of a cake or pie. Such icons could be available for quick access and organized by users to reflect their interests and areas of focus. A user or Stakeholder selecting an icon could, for example, insert it into a CPE
and/or open a faceting interface where the users could then select one or more subcategories for use in a CPE, or, for example, employ a stepped, further refined selection process.
Domain category selection supports user and Stakeholder expression of interoperable, interpretable, standardized Core Purpose and other CPE specification processes, as well as in some embodiments supporting similarity matching operations between user purpose expressions associated with any Domain category specification set which may be absent verb sets, that is absent Core Purpose set specification, and where, for example, verb sets are inferred from other context, history of like category user activities, and/or the like, for example, someone who owns a home that is already landscaped and has been using a landscape service, might, with some embodiments, default to landscape service when landscape or landscaping category is selected, since the property is already landscaped given the systems knowledge of the user.
As discussed, with some embodiments, expert arranged user interfaces provide choice and/or recommendation opportunities for navigating through and selecting action by user and/or Stakeholder sets. This may be supported, for example, in the form of faceting interfaces providing, for example, a classification structure for one or more Domain categories or as general purpose category arrangements that users and/or Stakeholders may use to associate one or more category sets with one or more PERCos verbs for specifying a Core Purpose set.
In various embodiments, Core Purpose specification capability through combining one or more verbs and one or more Domain categories is particularly useful in purpose approximation for similarity matching with Big Resource purpose classes, resource classes, and/or Big Resource resource instances and/or portions thereof. Users and Stakeholders use such Domain category specifications to focus on one or more verb and/or verb equivalent abstractions, such as learn, teach, purchase, sell, purchase, travel, consume, feel, want to swim, want to play, need to study (and other want to and need to permutations and/or the like), work, design, share, collaborate, communicate, and/or the like, with an operatively appropriate Domain category set, such physics, piano, chair, Chinese food, and/or the like. Such Domain category specification can be supported by generally known and accepted category organization information arrangements such as Domain category classes, whether inherited and/or relational and/or some combination thereof, and/or alternative information structures such as another ontology design or Lexicon set.
Such system sets with some embodiments represent expert (and/or authority, such as standards body) logically structured category information structures available for user and/or Stakeholder evaluation and/or selection, such as when proffered as a choice set by a faceting interface for specification of a Core Purpose and/or other CPE.
Category faceting can with some embodiments rely on classical Aristotelian approaches, in which category items are mutually exclusive and in the aggregate complete as to a general system, or for example, to a high level Domain within a system. Users can use, for example, an interface such as a faceting list to select a category, then, for example, a subcategory. A faceting interface may allow plural categories to be identified and conjoined, either in sequential faceting steps or collectively presented on screen (multiple faceting selection columns). Faceting selections could be made such as "chemistry" + "material science" +"silicon"+
"solar" with the verb "learn" to form a Core Purpose having a compound category set. The foregoing, if specified on a command line, might use an operator such as "+" to combine the categories, and the categories might be respectively weighted for contribution to processing if desired, for example associating values 1 through 10 to a given category selection through a right mouse button pop-up selection, with categories defaulting at 5 if no selection is made (or using other values as an application might provide). Similarly, multiple verbs might be conjoined using a verb faceting choice array. Further, a faceting interface might default to displaying next to a faceting list selection, a second level faceting list of "members" of the first list, with subsequent level lists available as desired. With some embodiments, frequently used Core Purposes, and/or Domain category and/or other CPE sets, may be saved and published for local and/or distributed/published use, as desired, along, if desired with symbolic icon representation of each such Item, for quick access as a PERCos Construct. PERCos Domain categories may employ prepositions as operators as faceting list choices, for example, activated by a right mouse click and drop down menu choice and/or by selection of a Desktop item for prepositions represented by a symbol/icon and/or test label and/or the like. Alternatively, a faceting arrangement may, for example, present a choice list where "to play" may be adjacent to the category base word "play" for the Core Purpose "learn to play music" involving the verb "learn"
and preposition "to" and the conjoined categories "to play + music."
In various PERCos embodiments, Domain categories and subcategories function as the "base"
focus of Core Purpose specification, with one or more verbs functioning as the user set activity perspective, with, for example, adpositions functioning as relational clarifiers. Whether or not used, for example, in combination with PERCos other Master Dimension Facets and/or resources and/or resource classes (including Constructs and/or Construct class sets), the intent of these capabilities in many PERCos embodiments is to, for example, constrain choices to practical standardized approximation operators that as a set and in combination maximize ease of use, including simplicity of choice and operation; maximize interoperability, consistency, and reliability; and/or support practical efficient Big Data and Big Resource approximation computing through purpose approximation and associated resolving to purpose neighborhood results for user/computing arrangement adaptive, unfolding processes to optimal interim results and/or Outcome.
In certain embodiments, PERCos category one or more information arrangements , whether in the form of lexicon, class, and/or ontology arrangements, are at least in part determined by Domain category and/or purpose class experts and/or standardization authorities. Such information arrangement determinations may supplement a standardized, general, common purpose base PERCos lexicon (and/or base expertise level lexicon such as corresponding to a base medium sophistication level for a given Purpose class and/or Domain category class set).
Such experts may, for example, be employed as consultants and/or employees by one or more of affinity groups and/or standards groups and/or commercial group and/or the like as described above and/or may be contributors to the standards activities of any such groups. With some embodiments, such experts attempt to, given their insight into the nature of use of verbs in their domains, define a constrained, and therefore simplifying standardized list or relational arrangements, which can be used, for example, in user and/or Stakeholder Core Purpose Expression or other CPE specification activity in PERCos purpose approximation for similarity matching and other shared and common purpose computing functions.
With some embodiments, input other than verbs and/or Domain categories may provide a basis for specifying Core Purpose input, such as user historical, crowd behavior, biometric signals, and/or the like derived information. The foregoing may provide a contributing or determining basis for inferred verbs, Domain categories, and/or combinations thereof. For example, it may be visually recorded that each time a user listens to a certain type of music, he may be enjoying the experience ¨ this may be visually interpreted by analysis of user expression, body language, spoken voice tones/frequencies and/or cadence, spoken words in conversations with other people present, and/or the like. This association of reaction to a resource set may be inferred and stored individually associated with a portion or all of the then current resource set and/or stored in the aggregate with one or more resource classes and/or purpose classes and/or similar logical groupings, with such resource set and/or class and/or other type characterizations being available to match with subsequent user purpose expressions, including using such information with Al processes to evaluate potentially most satisfying resource sets, portions thereof, and/or how user interface functions with resource sets.
Contextual Purpose Expressions (CPEs) are specifications representing respectively user and Stakeholder purpose concept approximations. In some embodiments, these approximations are specified to approximate user perceptions, user intent, and/or user classes.
In certain PERCos embodiments, CPEs have, at minimum, at least one verb or verb equivalent representing user activity perspective and at least one category representing the subject upon which at least one or more verbs is conjoined, the set representing a Core Purpose specification.
Such Core Purpose CPEs may be augmented by various other information sets. For example, in some embodiments, Core Purpose's may be augmented by Master Dimension Facet conceptual approximation perspectives and/or by auxiliary Dimension information. In some embodiments, CPEs may be particularly useful in characterizing purpose approximations relationships of resources and in identifying purpose responsive resource neighborhoods that may optimally support user learning, discovery, and/or experience purposeful processes and Outcomes.
CPEs may be prescriptive, specified by users as a characterization of, as well as any specified pertinent conditions regarding, a user set computing arrangement objective set, or they may be published as descriptive CPEs, specifying qualities related to a given resource set that may correspond, at least to a degree, to user CPEs, that is correspond to user purposes and specified other concomitant contextual considerations. Prescriptive CPEs are specified by users to characterize their purpose approximation concept set; they are ephemeral unless published by a user as a resource, or otherwise saved. Descriptive CPEs are published as the subject of, or are published in association as descriptive of, a resource set, including individual one or more resources and/or resource classes.
For example, resources may have one or more CPEs which describe Stakeholder purpose set one or more characterizations they declare as associated with a resource set, including, for example, a resource class set. These characterizations may, for example, portray a resource publisher or other Stakeholder set's perception of anticipated user CPE specifications and/or associated useful information for use in user and/or PERCos Coherence evaluation of a resource sets suitability -- which may include, for example, relative suitability in relationship to a plurality of resources -- for user purpose fulfillment, including for use in correspondence matching between resource associated descriptive CPEs and user CPEs representing user purpose approximation input. Descriptive Stakeholder purpose expressions may also frame publisher and/or other Stakeholder governance, commercial, value chain function, automation, process automation, event triggers to any of the foregoing, and/or any other administrating, constraining, and/or other regulating variables related to such Stakeholder interests, including, for example, rights management, financial budget and/or other information to usage, and/or the like. For example, these Stakeholder specifications may be included in a CPE set framing any such Stakeholder interests as related conditions for, and/or instructions regarding use of, a resource set. As such, some embodiments of PERCos will support the specification of, for example, affinity group or commercial organization process automation instructions that are specialized Constructs that may, for example, within a corporation, or within an industry group such as a trade group or association, or with a club, or as specified by a government within its sovereign area of control, state that, for example, if a then b or any degree of complex derivation thereof. This allows for event based process control functions to be embedded in CPEs and/or Stakeholder Purpose Statements. In some embodiments, such embedded instruction set may be associated with one or more Core Purposes, other CPEs, Purpose Statements, and/or PERCos Dimension information, such as Facet information and/or any auxiliary Dimension information, including to a purpose expression set associated descriptive CPE and/or Purpose Statement set that may be used in similarity matching and/or user evaluation of their associated resource sets, to help ensure that the consequences of such embedded instruction set are consistent with, and/or otherwise contribute appropriately to, user purpose fulfillment considerations.
A published descriptive CPE is published, at least in part, in anticipation of its potential usefulness in supporting users in determining correspondence to, or otherwise determining sufficiently similar relationship with, potential users' prescriptive CPEs and/or Purpose Statements, thus enabling PERCos Coherence (and/or other) matching, either in the form of complete matches or otherwise in the form of, in accordance with associated specifications, relative degree of similarity matching. Such correspondence and matching processes may be applied uniformly between CPEs and/or Purpose Statements, and/or may, in some embodiments, be evaluated according to rules comparing subsets of such prescriptive and candidate descriptive CPEs in differing manners.
PERCos Master Dimension Facet variables represent conceptual simplifications that supply contextual information in a standardized, interoperable form. Such Dimension information adds conceptual perspective characterization to CPEs, and/or may add such characterization to Constructs such as resonances, Foundations, Frameworks, and/or the like through their associated purpose expressions. Master Dimension Facet specifications enhance insight into the purpose approximation objectives of users and similarly provide additional framing parameters for descriptive Contextual Purpose Expression specifications by Stakeholders.
PERCos Dimensions can provide broad logical groupings of contextual variables for simplification, ease of use, and/or standardization in the formulation of user CPE contextual perspectives as well as the creation of operative Purpose Statements. They are relationally relevant simplification groups for providing purpose concept approximating values. They may be used to portray orienting user approximating Dimension Facets so as to purposefully direct human/computing arrangement activity. PERCos Master Dimensions and Facets, as well as auxiliary Dimensions, can be used to form more contextually rich Contextual Purpose Expression approximation specifications identifying conceptual neighborhood sets for relevant resource and/or resource portion similarity matching in support of user set learning, discovery, process automation, and/or experience unfolding.
In some embodiments, such contextual Dimension variables may be in part or whole "ignored"
in the response to rules and/or in the absence of pertinent corresponding prescriptive CPE user purpose expression information ¨ that is, for example, PERCos matching may be in part based on the presence of certain Dimension and/or Dimension Facet specification indicated in a CPE

and when or if some of such specific or comparable Dimension or Dimension Facet information is absent from a prescriptive purpose expression (including, for example, a Purpose Statement) but present in a descriptive resource purpose expression, its presence in the descriptive expression may be ignored in similarity matching or such non-corresponding descriptive expression portions contribution to similarity computation may be attenuated by application of desired instruction information to producing results based upon such instructions to ignore, attenuate, and/or otherwise transform such expression portion(s) set's contribution to a result set.
Further, in some embodiments, PERCos may support selective differing processing of instructions for different purpose expression portions. That is, such instruction information may be collectively applied to a CPE as a whole, or the whole or any portion set of any such instruction set may be applied to one or more subsets of such descriptive purpose expression subsets missing from prescriptive expression values and such applications may apply variably in differing one or more manners to different one or more subsets of such non-corresponding CPE
information. This ability to ignore, attenuate, and/or transform the input of such "missing" from prescriptive expression comparable or relatively corresponding expression portions, and the ability to process such items in a selectively differing manners, allows for expression subsets in resource descriptive purpose expressions that may not be consistently germane to overall, for example, current session, specific user purpose considerations for similarity matching to user purpose expressions and therefore are processed in some instruction managed manner so as not to interfere with relevant, that is in some circumstances more significant, similarity matching to subsets and/or subset combinations that may populate user purpose expressions.
PERCos Master Dimensions, through Facet and any associated value set specification, and as may be augmented by auxiliary Dimensions, provide PERCos processes with specifications reflecting the nature of user purposes, that is factors to be considered in producing PERCos processes and Outcomes that support users' respective purpose session sets. In certain PERCos embodiments, these factors may be specified at least substantially through the use of Dimension members called Facets, and any associated Facet values, describe generalizing principal features of a user sets' purpose focus and specified context conveyed in a standardized interoperably interpretable manner. These features reflect user conceptual approximation of their objective set as a basis, for example, for learning and/or discovery and/or experience unfolding, where at least material portions of such purpose characterization specified by a user set is performed by PERCos providing logical grouping of characterization considerations. These logical groupings may in some embodiments, for example, and as organized by standardized Facets, be selected, for example, from a Faceting or comparable selection list of respective Facet choices, and where such list may be constrained in some embodiments to provide only such standardized constrained choices as logically reasonable for such approximation and simplification purposes.
For example, in some embodiments, Core Purpose, or Core Purpose and one or more supplementing Master Dimension Facets and values -- which either of the foregoing may be augmented by auxiliary Dimension information and/or any complementary input, such as stored profile information, preferences, usage history, crowd behavior history, resonance set, including synergy instructions, and/or the like -- may form the basis for calculating approximation spaces that may be determined to hold, or otherwise correspond to, pertinent resource class and/or instance sets. These information intersections may be represented by corresponding spaces that may be populated by candidate resources, and where such spaces may be operatively represented by one or more most closely, similarity matched purpose classes or calculated purpose neighborhoods determined through correspondence analysis between prescriptive and descriptive purpose expressions such as their respective CPEs and/or Purpose Statements, and, when desired, with augmenting information.
PERCos, in some embodiments, thus can enable users to represent user classes through concept focus and context integration through prescriptive CPE specification. Such specifications may then be used in similarity matching with similar purpose expressions associated with purpose, resource, and/or participant class sets and/or instances and/or combinations thereof. This process may, in some embodiments, contribute to identifying, evaluating, prioritizing, selecting, combining, and/or provisioning one or more such classes and/or instance sets, resource members and/or member portions of which may then be prioritized and/or filtered according to at least a portion of the associated user Purpose Statement set so as to provide displayed, otherwise managed, and/or provisioned resource member and/or portion sets. Such resource member and/or member portion sets may represent sets associated with their respective parents classes or may be integrated, from multiple such class sets so as to produce a user purpose, Purpose Statement responsive neighborhood member set.
PERCos similarity matching processes may in some embodiments support two or more stage similarity matching sequences, where, for example, one or more purpose class and/or other purpose neighborhood sets are first identified, then another similarity matching sequence is started automatically or on instruction of a user set. For example, when PERCos Master Dimension Facets are used by users as a conceptual basis for selecting, and/or for specifying a CPE set which is then intended to be used in a multi-step matching operation sequence, Master Dimension Facets information can, for example, first be used for similarity (including for example, directly) matching with purpose class sets and/or other calculated neighborhoods containing resources declared as members by Stakeholders such as publishers and/or Repute Cred assertions. In some embodiments, this may be followed by further identification, prioritization, evaluation, selection, combination, and/or provisioning applied to all, or a selected germane subset of, members of such identified purpose class and/or neighborhood set. For example, further purpose expression and/or related information, for example from auxiliary Dimension and/or other embodiment Dimension information and/or from user, user group, and/or crowd related purpose expression related profile, preference, historical behavior, and/or the like information, may be employed so as to identify, filter, prioritize, evaluate, compound, and/or otherwise process all or a portion of information regarding members of a purpose class and/or neighborhood set, where such second or more stage similarity matching involves matching against metadata and/or constituent data of such resources, for example in the form of indexed and/or relational database stored information. The foregoing may, in some embodiments, enable users to perform more detailed and/or nuanced characterization of their purpose set which may be performed efficiently on the constrained set of resources comprised of, for example, first stage purpose class and/or other neighborhood results.
This means that such auxiliary Dimension information employed with user purpose expressions may provide, for example with some PERCos embodiments and under some circumstances, unstructured, non-standardized Dimension information that would be impractical or inefficient to employ with Big Resource (or other large, distributed information stores), but with the highly constrained interim result set following determining a purpose class or other neighborhood set, would now provide practical, efficient further parameters for use in evaluating, for example, meta-data indexes and/or the like, to arrive at a more precise, less approximate, result set.
Such two (or more) phase processing may be performed in a manner transparent to users, but provide users with the powerful benefits of purpose related standardized approximation processing followed by further evaluation using unstandardized (that is not PERCos standardized expression elements) and/or partially standardized, for example, auxiliary Dimension information. That is, some PERCos embodiments, for example, may employ a segmentation of user set CPE and/or Purpose Statement, for example, a set of Master Dimension information, for a first matching set, followed by, auxiliary Dimension and/or related information (such as preferences, profiles, crowd, and/or history related) for a second matching process (and which second set matching in some embodiments may be augmented by Master Dimension information in contributing to calculating the evaluation, such as for a prioritization, of a member set that may result, at least in part, from such first matching process). In such embodiments, this further matching, when using, for example, auxiliary Dimension information, may employ non-standardized elements, but since the group of resources to be analyzed is now a greatly constrained set resulting from, for example, a first matching process, in contrast to Big Resource or other large, diverse information stores, such further matching process, for example involving Boolean open text expression, can now be practical and efficient since the focus is on a specific resource neighborhood set calculated to appropriately correspond to a user set purpose approximation specification set.

Users may, in some embodiments, be able to review, for example be presented with, purpose class and/or other neighborhood members, evaluated and prioritized for example in accordance with standardized Master Dimension information, including for example, Core Purpose information, as well, for example for comparison purposes, be presented with the results of further second stage processing using at least in part auxiliary Dimension information, which when both result sets are provided to a user set, such user set may identify opportunities to enhance and/or modify their auxiliary Dimension information to reflect an unfolding, knowledge enhancement, and/or experience preference development. PERCos may also provide, in response to a single common, or two related user input processes, the results of "traditional"
search and retrieval technologies along with PERCos resource and/or resource portion identification, evaluation, prioritization, selection, combination, and/or provisioning as described herein, allowing for differing views into response sets resulting from purpose managed information systems and traditional, distributed web pages and/or other information resources.
For example, a user might be exposed to a split user interface window, or separate windows, with for example, each modality occupying separate windows or window portions.
Alternatively, a PERCos environment or traditional environment running a PERCos purpose class application may support toggling between a search and retrieval modality (e.g. Google, Bing, and/or the like) and a purpose based modality using techniques and interfaces described herein. Such an approach might provide user flexibility between performance optimized retrieval modes and learning, discovering, and/or experiencing enhancing purpose related PERCos modes. For these purposes, PERCos might transform a user CPE into traditional, Boolean unstructured text expression for use by such search and retrieval mode or may support a user set providing for example, unstructured, Boolean input. Boolean open text expression can now be practical and efficient since the focus is on a specific resource neighborhood set calculated to appropriately correspond to a user set purpose approximation specification set.
Core Purpose and Dimension Facet generalizing features may function, for example, as concept simplification vectors or axes corresponding to human conceptual purpose factors, such as, in an example, a verb representing a dynamic orienting user perspective factor such as "learn", a category representing a thing, type, and/or place such as "biochemistry", a user characteristic relative to a Contextual Purpose Expression describing user expertise/sophistication, such as "moderate" (versus beginner or expert), and a resource characteristic relative to a Contextual Purpose Expression describing a resource, for example, as "complex" (versus simple or medium, and for example, describing the complexity of material relative to a sophistication level).
Together, these approximation simplifications may be treated as axes used for similarity matching with, for example, comparable purpose expression information associated with purpose expressions and/or class index sets, resource sets and/or resource class index sets, and/or the like.
These PERCos tools discussed herein in some embodiments may be combined with various web information management related tools, such as search and retrieval, semantic web, knowledge graphs and clustering, expert systems, and/or the like. Such tools without the use of a PERCos technology set, may fail to provide reasonably appropriate resources, much less optimum resources, and optimum resources may seem to, and practically be, unattainable, given the nature of such web information management technologies, at least in practical timeframes and with sensible amounts of effort. PERCos technology can, for an example, combine the operative perspective of a verb set from one or more constrained verb lists, combined with focusing domain category one or more sets, and complemented by suitable user, resource, and/or Repute one or more Dimension Facets such as described herein, and when, as appropriate, augmented by similarity matching with purpose class one or more arrangements, can transform Big Resource, and what may appear to be boundless information diversity, location, and attributes, to manageable, very useful user purpose related sets, which can be further narrowed according to further processes involving subsequent similarity matching, Repute recommendation, fit to history, fit to crowd, Al support, and/or incorporation of user nature and priorities related information.

In some embodiments, purpose expressions, in the form of Contextual Purpose Expressions, include Core Purpose Expressions, which may be further combined with Master Dimension Facet and/or any other PERCos compatible associated specification one or more sets (for example auxiliary Dimension information) provided, as specified by users or Stakeholders and/or their PERCos computing arrangements, for the formulation of their CPEs and/or Purpose Statements. The foregoing specification information may optionally, for example, include specifically identified resource items such as participant, Construct, symbol, one or more instances and/or type resource classes, and/or, for example, may include instructions for facilitating resonance purpose optimization, process automation, societal/affinity rules events, thresholds, and management, and/or the like. Such expressions may optionally in some embodiments use, for example, conjoining operators such a "+" "-" "and" "not", specification instance contribution weights and/or other instructions, and/or clarifying/narrowing adverbs, adjectives, prepositions, and/or the like. Descriptive adjectives may, in some embodiments be limited to, and/or particularly adapted for use with, auxiliary Dimension expression elements such as with Constructs, resonances, process automation, and/or the like.
Further, constrained, preposition, adverb, and adjective lists may be employed and such lists may be constrained, at least in part, according to appropriate usage in a given Domain by an expert set and/or other authority/utility/standards set and such may be in some embodiments standardized such that, for example, one adverb, adjective, and/or the like may, as with categories, function as an approximation where the use of other similar terms or phrases would be treated as synonymous, as for example, as defined by experts and/or one or more standards bodies and/or the like.
Flexibility of use, or the absence of use, of adjectives, adverbs, prepositions and/or the like may be determined by experts and/or one or more standards bodies based upon their ease of use, simplification, standardization, and/or approximation priorities. For example, as may be considered appropriate in some embodiments, prepositions and/or adverbs may be available for user choice, for example as may be logically appropriate as associated with a Core Purpose set, but no, or a very constrained list of, adjectives would be available, or would only be available for use, for example, in auxiliary Dimension expression to reduce complexity and serve approximation objectives. In some embodiments, such constraint of available prepositions, adverbs, and/or adjectives, as discussed herein, may alternatively and/or in addition be Core Purpose, verb, and/or domain type and/or domain category specific constrained, that is constrained to options/choices normally and/or logically associated with such element, such as, for example, might be presented by a faceting interface context specific choice set for user selection. For example, the adverbs "softly" and "daringly" would make very little or no sense combined with a Core Purpose "learn nuclear physics," while the adverbs "quickly" or "visually" could be informing clarification. For example, in some embodiments, domain experts can readily identify highly constrained adverb lists for use with very specific verb sets, making simplifications for faceting and/or comparable user interface modalities easy and efficient for users and Stakeholders alike, thus facilitating PERCos simplification and concept specification.
Similarly, adjectives (for languages that have adjectives) can be identified in a constrained manner for specific and/or classes of Core Purpose. For example, many types of adjectives may be inappropriate for use in PERCos purpose concept approximation with Core Purpose sets, or, for example, with Core Purposes as might be complemented with Master Dimensions Facet information, though such adjective use might be expert determined to be appropriate when used with auxiliary Dimension expression components. For example, in some embodiments, adjectives such as "rich" or "fastidious" may be decided to be inappropriate simplification choices for "learn nuclear physics" or "evaluate + purchase Italian car," but for example "fast"
and "affordable" are logically appropriate options. As with prepositions, language experts and/or applicable Domain Category experts (such as experts in Science (or, for example more specifically physics), Cooking, Plumbing, Auto Mechanics, and/or the like) can readily screen and limit adverb and adjective and/or the like to practical, quite limited choice lists for easy user approximation specification selection, and such limitation may be determined to be appropriate when applied generally to CPE expressions, domain category specific, or purpose expression type specific (Core Purpose, Core Purpose plus Dimension information, Core Purpose plus Master Dimension Facet information, and/or the like in any reasonable combination). In some embodiments, this capability may be particularly useful for users and Stakeholder ease of use and approximation specification using PERCos simplification techniques for choice selection respective to specific Core Purpose and/or other CPE sets, such as those association with a CPE
associated purpose class, including for example, when specifically adapted to specific one or more purpose class application given their anticipated user profile information and/or purpose expression specifications.
In some embodiments, such choice management of verb, category, Facet, and other list types, can be constrained and/or otherwise organized as reflective of the sophistication of a user in a given purpose context. For example, if a user is unsophisticated, for example, in the area of global economics, the set of category terms, for example in purpose related to such area, may be simplified and constrained when relating to some PERCos embodiment interfaces for activities for category related purpose fulfillment. Such constraining and/or shift in organization presentation, can be based upon such user's purpose and/or domain specific characteristics, that is with each purpose or category domain shift, a different "level" may be employed in use interface operations.
PERCos embodiments may, as associated to such a level of specified or assumed expertise/sophistication/knowledge and/or the like, provide for user Facet and/or other choice selections that are automatically or by user selection provisioned, and where such choice option proffering or automatic provisioning may be associated with at least a portion of such user's characteristic set. For example, such a dynamically adjusting framing of choices option may be selected by a user, or by a user employer corporation or by other organization types, such as an affinity group or association. Such adjusting choice options may be in accordance with specified or presumed user "levels" as associated with a purpose or Core Focus set and an information structure may store such associations with sets for user (and/or user groups).
Such purpose or category adjusting level option arrangement may, for example, be defined and/or organized as a web service by domain or general experts, such as ontology and taxonomic academics and corporate professionals. Such capabilities can be embedded in purpose class applications, plug-ins, operating systems and environments, and the like, which may inspect user information, such as user profile and/or user preference information (such as a request to use contextual adjusting such levels) and/or history of PERCos embodiment usage. In some embodiments, the level may, for example, be at least in part determined by an analysis of estimated relevant user characteristics from some or all such information, and/or the like.
In some embodiments, users may select a characterized resource set by selecting an icon or some other symbolic representation of such resource set where such symbol was published by such Stakeholder, e.g. a resource publisher, as a branding, purpose characterizing, and/or other identifying representation. Users may also publish for their own use (and/or may publish as Stakeholders) Frameworks, purpose class applications, Foundations, resonances, CPEs, and/or other Constructs and associate any one or more of such Constructs with representative symbols for simplification of use, for example, when wishing to associate a group of symbols with a purpose class or other neighborhood. For example, purpose class applications and/or other Constructs by their type and/or collectively, may be organized by visually similar symbols, such as using the same symbol in differing colors, for all Participant sets, including Participant class, Construct use in association with a specific CPE or associated purpose class or the like. A user may specify one or more Core Purpose and/or other CPE combinations and associate a symbol with such specification whereby resources employing such specification may automatically have such symbol associated with them, and where such symbol may be varied in some manner, such as font used for descriptive name, color, size, display orientation (e.g. off axis by a consistent amount per usage association distinction). The use of any symbols representing Constructs herein, may in certain embodiments, produce, that is extract from or otherwise transform such symbol to, its associated purpose specification, enabling such symbols to be inserted as shorthand into purpose expression specification and/or the like, and where such symbol may provide its corresponding specification information as input to other user purpose operations.

In some embodiments, Purpose Statements represent transformations of user CPE
specifications where such transformations are effected at least in part as a result of processing input regarding user, user group, and/or user affinity group or other association preferences, profiles, PERCos usage history, PERCos and/or other crowd behavior information, user biometric input, intelligent tool input such as Al, and/or any other PERCos Purpose Statement input specification. Both CPEs and Purpose Statements may be employed in similarity matching to descriptive Contextual Purpose Expressions and/or descriptive Purpose Statements, depending upon the operational specifications. Similarly, Stakeholder CPEs may be transformed, at least in part, into Purpose Statements through the provisioning of Stakeholder profile and/or preferences information and/or one or more input types as described above (excepting user biometric information would instead be Stakeholder biometric information). Such preferences and/or other information types described above for users and Stakeholders, individually and/or as sets, may be associated with, for example, resource set, including resource class and/or resource portion sets, including for example CPEs and/or purpose class sets, Participant and/or Participant class sets, Constructs and/or Construct classes, and may include instruction information sets that are resource sets or, as may be employed, are directly provisioned, are non-published, and/or non-PERCos published. Such instruction sets may include, for example, resonance specifications, process automation information, such as commercial process automation event based instructions for Stakeholders interests, privacy right and/or security instructions, and/or financial budget management event based triggers and instructions for users, and/or the like.
In some PERCos embodiments, Master Dimensions provide key logical groupings of Facets and any associated values simplifications assisting users and Stakeholders in representing their purpose approximations. PERCos supports various embodiments of Master Dimension and Facets, with an exemplary embodiment detailed below.

A primary objective of Master Dimensions and Facets is to provide a simple apparatus and methods for users and Stakeholders to specify CPEs representing practical approximations that produce corresponding purpose fulfilling resource sets and/or resource portion sets. Such resource information, in some embodiments, may be particularly useful when the learning and/or discovering of approximation related resource sets may lead to user awareness of resource options and associated specific purpose fulfilling user purpose interim results and/or Outcomes. Resource portions (including information derived at least from such resource portions) may be of particular interest when working with a resource, such as a purpose class application, in order to realize a specific Outcome, that is a user purpose process end result set, where such one or more resource portions may be specific information one or more instances provided by the purpose application as specific to user purpose knowledge/information enhancing and/or evaluation.
Master Dimension logical groupings may comprise, for example as an embodiment and without limitation:
1. Core Purpose Expressions, including verb and Domain category groupings to approximately characterize key focus for core user and/or Stakeholder Core Purpose objective area(s), and where such verb list may, in some embodiments, be a substantially constrained list of verbs representing a practical and manageable array for user selection, and where in some embodiments verb sets are arranged as approximate synonyms, and where such approximate synonyms may operably correspond to a consistent operative "representative" (which may or may not have a user interpretable form). In some embodiments, verb choices may be limited, or further limited, based upon prior user history information regarding PERCos use and/or based, at least in part, on a category selection made during a prior purpose related PERCos step set to such verb selection, where such constraining of verb selection choice was, or is being made in a consultative manner, formulated by intelligent analysis of the association of such verbs with such category options, made by general and/or domain experts, and/or by other one or more authorities, and/or the like, and such curbing of selection options is based upon at least one of user and/or Stakeholder ease of use, simplification, logical framing, approximation efficiency and/or value, and/or the like considerations.
Similarly, if a verb is selected first during a PERCos CPE specification process, category options that may be available may, for example, in some embodiments, be limited to such categories that may be based upon at least one of user and/or Stakeholder ease of use, simplification, logical framing, approximation efficiency and/or value, and/or the like considerations, and such category curbing determinations may be made by general and/or domain experts, and/or by other one or more authorities, and/or the like.
2. User Characteristics, for specifying principal user characteristic considerations as evaluative and/or filtering variables as contributing input for identifying purpose class sets (which may be publishers as PERCos resources) and/or other neighborhoods and/or resource instance sets. Such Facets may comprise, for example, sophistication level specification related to user purpose, such as beginner/moderate, advanced;
user age such as ranges (20-30, specific year) or textually name age periods such as senior, middle age, young adult, teenager, and/or the like; user language, such as English, French and/or the like; time or time range (e.g. time budget available for usage and/or for resource publication payment related fee(s) and/or the like); financial budget (dollar amount available to be applied, desired amount to applied; education degree level (e.g. BS);
education degree category (e.g. chemistry) and/or the like, which may be specified in one or more ranges); breadth of approximation results, that is for example, use higher order rather than lower order super or relational class one or more sets for selecting and/or prioritizing member resource sets, for example, candidate PERCos process results resource candidates, where the foregoing may be user specified by selecting from, for example, "broad, medium, or narrow" as to the size and flexibility extent of the Coherence and/or other PERCos Services (and/or or published) net results for candidate resources in response to a user purpose fulfillment process set. This provides the option for more or less generalization and broader set of resource candidates as may be circumstantially specified as appropriate; and/or the like and where one or more such simplification Facet categories are standardized for interoperability, approximation computing, and Stakeholder and/or user and/or other party ease of use and which, for example, may rely on Facet constrained user and Stakeholder choice selection sets and/or numerical value input.
3. Resource Characteristics, including, for example, length (e.g. short, medium, long, very long); size (e.g. pages, megabytes, time to play, as, for example, numeric values);
availability (immediate, time period (e.g. range, estimate, in days); cost (e.g. price individually, in volume, to specific groups); complexity (e.g. simple, moderate, substantial); sophistication to purpose (beginner, moderate, advanced);
Quality to Purpose (for example, from certain Aggregate Cred ratings overall, to quality type, to one or more author, publisher, and/or provider set (such as 9 out of 10 from expert EF
characteristic qualified domain specific reviewers for Cred assertion type);
Role of resource, such as standardized constrained list of types such as Contributing Word Processor, Domain specific encyclopedia, and/or the like); Compound resource, indicating whether a resource is comprised of contributing component resources (single or has multiple providers, publishers, authors, and/or the like); has rights and governance, indicating a resource is copy protected, open/unprotected, uses advertising, collects user information generally and/or selectively (as per contributing resource);
and/or the like and in such embodiment such simplification Facet categories are entirely or in other simplification supporting embodiments primarily standardized for interoperability, approximation computing, and/or Stakeholder and/or user and/or other party ease of use and which, for example, may employ constrained, that is limited and standardized Facet sets for user and Stakeholder choice selection sets and/or numerical value input.
4. Reputes Repute Creds provide for standardized, interoperable approximation assessments of resources, resources portions, and facts and/or non-resource items, all the foregoing treated as subjects of Creds as they are evaluated in relationship to specification and/or derived context, and in some embodiments where such context specification may be limited to purpose expression sets. Reputes are, in some embodiments, a form of resource and employ resource elements, but are listed in some embodiments as a separate Dimension because of the nature of the logically related functional distinctions of Repute use including certain distinctive qualities in specification, including Facet types, the foregoing for the evaluation of other resources.
In some embodiments Reputes may be particularly useful when Repute Creds, EFs, and/or FFs are employed in PERCos processing, such as Coherence and/or other PERCos Services functions, related to resource sets and/or resource portion sets, and where such resource items may be evaluated, prioritized, selected, provisioned, combined/or used with other resources, including provisioning evaluation and/or decision applied resource and/or non-resource use for one or more Roles in Frameworks (including class applications), and, for example, where such is at least in part based upon such Repute information. In some embodiments, Repute Creds, for example, carry information describing assertions made by a Cred publisher set (themselves and/or on behalf of a creator set) regarding a subject matter's, e.g. a reference book's, software application's, Participant's (e.g. human individual or group), hardware arrangement, computing environment, specialized device, and/or the like's, Quality to Purpose, Value to Purpose, Quality to Contribution to Purpose, Quality of Publisher to Purpose - or in general, Quality of Creator to purpose - or in general, Quality of Provider to Purpose - or in general, Integrity of Creator, Integrity of Publisher, Integrity of Provider, Reliability, in general context and/or to purpose (e.g. level of relative fault tolerance and/or consistent reliable operation) , and/or any combination and/or the like, and where one or more such simplification Facet categories are standardized for interoperability, approximation computing, and Stakeholder and/or user and/or other party ease of use, and which, for example, at least a portion of such Facet categories may rely on Facet constrained user and Stakeholder choice selection sets and/or numerical value input, such as choosing "level 7" or inferring such numeric value for Quality to Purpose from a choice variety of levels 1 to 10, and/or the like.

An EF is based upon subject matter being stipulated to, and is testable and/or has been tested to demonstrate, and/or has been issued by some trusted authority in some form that demonstrates that, the subject matter is factual, that is true or false. EF is declared an axiom that is a testable assertion treated as fact. FF is based upon a spiritually based belief and treated as an axiom. EFs, and in some embodiments and circumstances, FFs, may be employed with Creds as assertions regarding one or more characteristics of a Cred publisher, creator, provider, and/or subject matter. In some embodiments, Creds types may be selectable, where Cred type may be selected from a faceting engine interface, for example, as individual Creds, aggregate Creds, or compound Creds, as well as in the form of Cred on Cred, aggregate Creds on Cred, and compound Creds on Cred.
Creds in some embodiments may also take the form of derived Creds where assertion information in Creds is interpreted according to some rule set and transformed into an at least in part a derived form based on such rule set, which may include transformation of aggregate Cred information, and/or the compounding of differing but substantially similar Cred subject assertions to form an approximate aggregate Cred regarding a "higher level" subject matter inclusive of the subjects of such underlying Creds, for example employing a Cred using a broader taxonomic and/or ontological specification for its Cred subject, which may, for example, comprise a category superclass of the respective Cred subjects, which Cred assertions may be associated therewith.
For example, Cred sets on Italian Sports Cars, French Sports Cars, British Sports Cars, and German Sports Cars (e.g. fast, fun, and well handling vehicles) as to their Repute Facets Quality to Purpose and Reliability to Purpose may be aggregated to a derived aggregate Cred that forms an information resource published, in some embodiments, by a Stakeholder and/or by PERCos service, such as a cloud service or utility and/or the like, with the foregoing deriving such information automatically (and/or on user instruction) based on interpreting the subject matter of such certain Creds to be subject subclasses of European Sports Cars. Such derived aggregate Cred set might be useful, for example, in response to a user purpose 'Learn' 'Sports Cars' where sports cars form a category conjoined with learn to form a Core Purpose, such derived Cred information could be employed to input prioritization information regarding European versus Japanese sports cars, for example, if it specified a derived aggregate Quality to Purpose value or a reliability in general value, for example, if a user set specified such Facets in their purpose expression information as information to be used in similarity matching and/or other evaluation processes. For Reputes, various embodiments may support differing levels of Facet choice selection options and/or value ranges in order to support shaping of user interface complexity to user priorities, experience, expertise as to Domain and/or purpose, and/or the like. As with other PERCos resources, generally speaking a less controlled, that is less constrained and more broadly flexible vocabulary may allow for more expression variability, for example in purpose expression, but may require, in some embodiments, synonym analysis and/or more extensive semantic analysis. Such tools may also be used if differing Cred purpose expressions and/or subject descriptions are to be interpreted for integration. PERCos embodiments, where resource subjects have unique identifiers, may be interpreted within the context of their taxonomical and/or ontological higher order grouping sets, for example using super classes having the applicable Cred subject classes as members and but where such Creds share Facet type assertions on their subject.
5. Special Facets represented, for example, by corresponding symbols and/or alphanumeric text whereby selection/entry of a special operator may, for example, include relevant preference, profile, crowd behavior (as, for example, related and relevant to a specific CPE and/or Purpose Statement ¨ for example as associated with a purpose class that such CPE is a purpose expression member, and/or as related to a CPE and/or Purpose Statement component expression set such as one or more included CPE Core Purposes).
A PERCos arrangement may include a constrained number of such symbols, which may in part be organized, for example, under Dimension simplification groupings such as one or more for each of the auxiliary Dimensions identified below, such as a set for Master Dimensions and/or Facets and/or respectively for more granular logical simplification groupings such as specific instances, classes, and/or other ontological groupings of any resources, which may include resource or any non-resource (if applicable to the item and when not specifically published as a PERCos resource) forms of Constructs, such as Frameworks, purpose class applications, Foundations, and/or the like; Reputes such as, for example, aggregate Creds (which may be through background processes automatically updated); resonances; profile information; preference information;
administrative programs and/or information; process automation operations;
specific societal/affinity group associated purposes; and/or the like; and where such symbolized items represented may be PERCos resources, including for example, purpose class application or application groupings. For example, a side viewing abstract image of a face might represent "insert relevant profile information." A constrained number of such symbols, for example as symbol for "insert expert recommend resonance information"
might be a general, expert system managed provisioning of resonance instruction information, and any associated data, for optimizing a CPE, and, for example, contributing to the formation of a related, optimized for user purpose operative Purpose Statement. Special Facet symbols/alphanumerics may represent and be consistently used as any user specific and/or Affinity group formulation (whereby, for example, such respective users and/or Affinity groups PERCos arrangement may translate any such Facet into one or both of PERCos interpretable and interoperable standardized PERCos expression information), and/or free form parameterization, which may then, as appropriate, be employed interoperably with other "external" PERCos arrangements.
Relational operators may, in some embodiments, be used in Dimension expression specification to clarify/enhance contextual simplification (prepositions e.g. "under, with, to" and/or the like, positions and/or durations in time or location, and/or adjectives including colors, size (big, medium, small, short, moderate, long), emotional attributes (happy, sad, exciting, unexciting, stimulating, challenging, thought provoking, counter-pointal).

While various embodiments may provide differing sets of PERCos purpose Dimensions with different logical organizations and simplification characterizations, including various ways of representing and/or modifying them, for example, within PNIs, the contextual organizational and expression simplifications can in some embodiments primarily derive from separation in certain logically related groupings, such as groupings of user descriptive information as that which most significantly reflects the general and/or purpose specific characteristics of one or more users, the characteristics which are associated with published resources, the characteristics associated with Repute, the qualities of context reflected by Core Purpose specification, and the use of special symbols/descriptive representations, all the foregoing allowing for, in some embodiments, standardized, interoperable, purpose expressions. Other embodiments that provide certain or all of the PERCos expression capabilities may support inferring of purpose from context, such as (a) inferring verb and/or prompting for verb selection, and/or other characteristic set, from a at least in part inferred, logically appropriate choice list, (b) use of synonym such as word and phrase thesauri, (c) semantic analysis, user and/or crowd behavior related to resource, purpose expression, and/or purpose class and/or neighborhood and/or the like.
These Dimension groups and Facets assist users and Stakeholders in easy logical specification processes; they may first identify what in many circumstances and embodiments may be a first user purpose expression activity, identifying a Core Purpose such as "learn Ford auto mechanics," which may then be followed by specification of certain Dimension specific characteristics, including the use of logically related Dimension Facet types, for example, within user characteristics Dimension Facets characteristics such as "medium sophistication/experience," and "time < 100 hours" and "budget <$200, which all the foregoing may be associated with the Core Purpose, followed by a user specifying, for example, resource characteristic, 'moderate' resource complexity' and further specifying Repute Cred "Quality to Purpose" (levels "4" out of a 1-5 choice set), then specifying a further Repute Dimension using a publishing category Faceting list associated with the Core Purpose with the selection of "major automotive publication" and "national/regional newspaper" as respective EF
characteristics of Repute Cred resource publishers.
As an example under an embodiment of a PERCos resource learning/discovery user CPE where a user set specifies using both Core Purpose and user and resource Dimension Facets:
"Core Purpose: (learning' + 'Applied Synthetic Biology Research Skin Tissue Replacement') + user Facet: Beginner to Purpose + user Facet: Education, College BS +
resource Facet: Time Frame P (for publication timing) > twelve months + resource Facet: Time Frame T (timeliness of underlying work) within 48 months; Repute Facet: Tenured Professors (in synthetic biology) Value to Purpose." In one embodiment, for example, a purpose class 'Learning Synthetic Biology" and a Category class "Synthetic Biology" are identified through similarity matching to the Core Purpose 'Learning' + 'Applied Synthetic Biology Skin Tissue Replacement' as the closest, in such embodiment, classes having members covering the Core Purpose focus area.
For example, the members of both classes can then be matched against an index for each of the classes matched against a purpose expression for the Core Purpose and standardized Facet values. An article in the hypothetical journal "Online Applied Synthetic Biology Updates," is a resource member of both classes, and is rated by such Domain tenured professors as the most valuable article for the less sophisticated, that is beginners, in learning about recent developments related to the Core Purpose.For the hypothetical example, the professors rate this particular article highly for the moderate and sophisticated, because it well serves the purpose of all Core Purpose interested parties, since it is very well written, has a concise overview in the beginning, and for the more sophisticated, has an extended section of more technical information. In this embodiment and with this hypothetical example, the second most highly rated resource through such same similarity matching for beginners with a college science education is a publication entitled "Introduction to Applied Synthetic Biology," Chapter 6, Skin Therapy.

As discussed, user purpose expressions may in some embodiments include, and/or may otherwise be transformed by (as, for example, in generation of Purpose Statements), non-standardized input such as, historical input, and/or auxiliary Dimension information and/or the like. Such auxiliary Dimensions, for example, do not employ simplification Facets since by nature they may take an unlimited or available in large numbers of possible forms. In some embodiments, information under these Dimensions are PERCos interpretable and employ standardized commands, syntax, and/or other language elements and which be supported and/or otherwise at least in part managed by one or more standards managing arrangements such as society, association, club, and/or utility sets. Some embodiments make employ resource, participant, Stakeholder, user node, and/or associated forms of meta-data and/or other information that may be in non-standardized form as contributing input into user or Stakeholder Purpose Statement or other purpose expression formulation, where such input is interpreted, at least in part, by some PERCos embodiments processes with the aid of semantic, expert system, and/or other tools and associated information stores.
Auxiliary Dimensions that contribute to contextual purpose specification augmentation may be embodied, for example, according to the following categories and/or the like combinations, for user and/or Stakeholder interface and concept simplification and expression purposes. Instances of such Dimensions and/or portion thereof may, in some embodiments, be employed as PERCos resources. An auxiliary Dimension example embodiment can take the form of:
1. Process Specifications: Published as resources, for example, as resonance purpose optimization facilitators, Process Automation instruction sets, Societal/Affinity instruction sets, auxiliary purpose expression building blocks, and/or the like, including, for example, a. Affinity/Societal instructions, including, for example, corporate, trade, club, political, nationality and/or the like related grouping characteristics (e.g.

involving groups as to their conduct and/or interaction, (e.g. sub-Dimensions policies/rules/laws, cultural mores or preferences, roles and/or hierarchies, and/or sharing, collaborative, participatory, and the like.) b. Process automation instructions, for example, instruction sets that in consequence to the use of one or more resource sets, provide, for example, input information to processes that influence non-PERCos same purpose session sequence processes in order to support realizing one or more results flowing at least in part from such instructions input and one or more associated processes. Such processes may be external to the PERCos cosmos, crossing a 3"d Edge (Et Edge with users, 21d Edge within PERCos cosmos such as inter PERCos digital communications).
c. Resonance specification instances, including synergy specifications, for purpose optimization, for example, computer software instructions for example, specifying one or more characteristics and any associated weighting and/or transformations used in Coherence purpose evaluation processes, where the presence of any resource associated characteristic set, including any associated values and/or weighting, may contribute to user purpose satisfaction and may be used to filter and/or otherwise positively prioritize a related resource set or class set, and where any specified other characteristics that may be considered to negatively affect user purpose satisfaction in a manner specified can be reduce in the matching priority of a given associated resource set or class and where any such resonance specification may be associated with specific purpose expressions and/or purpose classes and/or resources associated with such purpose expressions and/or classes and/or purpose class applications and/or with Affinity/Societal, Participant, and/or other resource instances and/or classes.
2. General Data Items and any associated instructions which may be employed generally and/or associated with any given specific resource set such as purpose, Participant, Construct, PERCos computing arrangement, and/or other resource items and/or classes. These data items may in various embodiments include published local and/or remote contextual resources, and/or data items. Such resources and/or data items which may be generated on demand from any such information, where such data items may be employed for PERCos computing arrangement internal usage, for example as may be the case with information extracted from user computing arrangement profiles, preferences, user usage history and/or related behavior, and/or the like information, and/or as more generally published, again as profiles, preferences, user history, crowd history, expert input, the forgoing provided in a form interpretable by, or transformable to be interpretable by, PERCos services such as Coherence. Data items may be represented by corresponding, user interpretable and usable expression symbols and/or alphanumeric representations whereby, for example, profile information or preferences information may be incorporated in purpose expressions through the selection of a corresponding symbol, such as an icon for user preferences associated with a user class and/or resource class.
3. PERCos Constructs: Published as resources as Foundations, CPEs (including Core Purposes), Frameworks, and/or the like.
4. Free form parameterization: for example, as may be specified in Boolean expressions, and which may be published as resources, and/or may be data-entered ephemeral information sets, where such may be processed as a separate set of purpose expression conditions and/or may be modifying one or more other Dimension sets, Facet sets, and/or other syntactically logical portion sets of CPEs and/or Purpose Statements.
The above Master and/or the like Dimension information may be complemented by biometric inferred information, indicating camera and/or audio and/or other physiological/physical observation/sensing analysis to provide mood and/or other reaction input.
PERCos may, in some embodiments, organize Dimension simplification and logical groupings around, for example, Core Purpose Dimension combined with process/outcome Dimension.
Such process/outcome Dimensions might take the form of:
Process/Outcome Dimensions:
1 Intellectual/Abstract (e.g., Dimensions thinking, knowledge/information acquisition, relational perspective enhancement/modification, logical processing) 2 Experiential (i.e., the experience, per se, such as Dimensions satisfying, happy, stimulating, long, short and/or specific time based, hot, cold) 3 Actional (the primary focus of a session is to take an action, that is Dimensions commercial, group, and/or personal purchase, publish, output a result, communicate, initiate a remote process) Other Process/Outcome Dimensions 1. Social/Interactive (e.g. Dimensions sharing, collaborating, co-participating, friending, communicating, supporting, engaging (e.g. a new friend), and the like.) 2. Acquiring/Evaluating/Developing (e.g., Information/Knowledge, and the like.) 3. Entertainment (e.g. Dimensions listening to music, having fun, observing (such as a sporting event), watching (such as a movie), and the like.) 4. Transactional (e.g., Dimensions include commercial, for example acquisition of goods and/or services, and the like.) 5. Affinity/Societal Group (e.g. involving groups as to their conduct, for example Dimensions policies/rules/laws, cultural mores or preferences, roles and/or hierarchies, and the like.) 6. Tangible (e.g., Involves instruction sets that in consequence to the use of one or more resource sets, provides input information to processes that influence non-PERCos purpose related processes in order to support realizing one or more results external to PERCos flowing at least in part from such instruction set and one or more associated PERCos processes, and the like.
Dimensions, with some embodiments, not only may provide logical scaffolding assisting users in outlining their purposes, but also may function as weighting and/or algorithmic expression groupings reflecting a user's composite purpose focus and simplifying and improving efficiency of PERCos processes and results, and in particular when used with huge to "internet boundless"
resource opportunities. In certain ways, such Dimensions may at least in part comprise a "Basic Level" common orientation, simplification means as commonly understood by users in a manner conceptually similar to Basic Levels in Postulate Theory. In some embodiments, such Dimensions, such as Master Dimensions, which are represented by one or more standardized Dimension Facets, can be expressed in any logical combination, and may comprise Master Dimension and their Facets and/or Dimensions purpose expression sets which may be augmented by one or more Dimensions attributes/values. In some embodiments, the foregoing may be supplemented in PERCos processing, at least in part, by otherwise normally interpretable natural and/or Boolean language expressions, with or without associated values.
Dimensions and and/or their specified constituent standardized components may, with some embodiments, be expressed, for example, with associated weighting algorithms.
For example, Dimensions may have user conceived weighting groups (e.g. with associated contribution values), for example a combination of Dimensions, comprising a Core Purpose arrangement plus, for example, Dimensions weighting of 90% Social and 10% Intellectual, or 25%
Intellectual, 70% Transactional, and 5% Experiential, or 50% Intellectual and 50% Societal.
Such Dimension attribute values may be employed in matching and similarity, prioritization, provisioning, and the like, as may at least in part relatively, or absolutely, correspond with comparable Dimension attribute values associated with resources, for example published by Stakeholders as germane descriptive information as expression components of CPEs.
For example, a user with a Core Purpose of Buy Camera might be primarily focused on the Intellectual (e.g., evaluative such as what are the important features, brands, models, specifications, comparative pricing and/or the like), and on the Transactional (e.g., actual venues for purchase and their requirements), or on the Social (e.g., acquiring, through communication with friends, their perspectives on candidate cameras), or on Sharing the transaction activity, such as buying together with a friend, and the like.). Similarly, if one wanted to go to a pop music concert and was evaluating options, one might emphasize Intellectual, degree of emphasis placed on evaluating options, Social, co-participating with certain friends, experiential, partying and dancing, and Transactional, how much and where to purchase and set priorities of 50% for Experiential, 20% for Intellectual, 30% for Social (right friends co-participating), and such input could then in some embodiments be combined, for example, with Repute input, CPEs, any stored profile, crowd behavior, and/or affinity/Societal information, and with any other Dimension input, to provide input to formulating an operating Purpose Statement for purpose class selection, matching and similarity, Participant (to become active users) selection, and/or provisioning, and/or the like. Such Dimensions specification may as above weight the Dimensions, and/or weight Dimensions Facets or attributes.
In some embodiments, the relative weighting of Dimensions can influence, in part, the treatment of various resources (for example, how Intelligent Tools, such as expert system faceting systems and/or at least in part Postulate Theory and/or related Conceptual System based class or other ontological systems, constrain and prioritize the offering of selections, and/or presentation of, verbs, categories, purpose Facets, and/or divisions) and/or how such Intelligent Tools support user identification, evaluation, prioritization, expression formulation and/or selection processes.

Specified combinations and/or other algorithmic expressions of Dimensions can be published and employed as resonance instruction sets associated generally with a purpose class. For example, high weighting in a social dimension might lead to increased weight being given to certain resources (including, for example, other participants) related to high resonance factors, e.g. going to a concert/dance with a Participant off a certain friend list, or having a Participant with certain personal characteristics indicating they were good dancers and good to party with, and where such resource characteristics would be responsive to resonance instructions.
A PERCos matching and similarity web service that can be supported in some embodiments is provided by one or more utilities, associations, and/or corporations, and functions as a rating service arrangement that, for example, for resource publishers and/or the like and/or web advertisers and/or participant information aggregators, create purpose relating information systems that associate resource instances and/or resources groups, including, for example, ontological and/or taxonomic and/or organization sets of resources, including any resource type, such as participants, with any type of purpose expressions and/or classes and/or other neighborhood groupings, where such association information may be augmented by other resource and/or purpose related data such as user and/or crowd related historical behavior system usage information, preferences, profiles and/or the like. For example, such processes may evaluate a Participant, when active as a user, related to a participant self-published Cred(s), related Cred EFs, third party Creds on the participant, and/or participant profiles, preferences, and/or use history, such as the participant has a Ph.D. degree in biochemistry, an avocation in near earth objects, and frequently learns about astronomy issues using Popular Science and some advanced science publications, wherein such participant as an active user specifies a PERCos CPE of 'Learn' 'astrophysics near earth objects' 'user Facet:
Sophistication 7' (on a scale of 1-20)".

Such a web service can manage methods that will process purpose expressions, including, for example, Core Purpose and such associated Dimension Facet and/or other available participant related information, including, for example, Dimension Facets and/or auxiliary Dimensions and/or the like and/or preferences, profiles, history and/or the like and similarity and/or other processes and evaluate such information against descriptive CPE and/or Purpose Statements and/or resource metadata, to identify most practical purpose fulfillment match, and/or, for example, priority ranking of candidate resources and/or resource portions, for that specific Participant as an active user expressing such a CPE and/or having such user's PERCos arrangement specific operative Purpose Statement.
Core Purposes are comprised of verb and category combinations, which verbs may be in some embodiments, at least at times inferred. Such Core Purposes may be augmented by the contextual Dimension Facets described in the following sections. Core Purpose conjoined verbs and categories, in some embodiments comprised of constrained verb options that are associated with category descriptions, such as physics/molecular, may be employed in some embodiments with prepositions and/or adverbs and/or other informing grammar terms, for example, selected from option lists through the use of, for example, faceting interface arrangements, and where the available grammar options are logically relevant, given the Core Purpose, and may be constrained in variety, for example most useful terms of a grammar type, so as to support the simplification and approximation capabilities of PERCos arrangements.
Similarly, for example, Domain category options may be constrained to those logically sensible given a user chosen verb set. Correspondingly, verb options may alternatively or also be constrained to those logically sensible given a given category specification, and/or in some embodiments may be inferred from a category, which may be presented as a short, e.g. "beef steak"
which might in some embodiments have the verb options of "purchase, cook, eat," while the conjoined categories or sub category "health" "beef steak" or "health beef steak" might have verb options of "learn, teach, communicate". For example, it may make sense to "learn" or "teach physics,"
but it likely doesn't make sense to "purchase physics". Similarly, while it may be appropriate to "research physics," or to "purchase physics textbooks," it may make no sense to "travel physics"

or to "meet physics textbooks." Language and/or Domain experts can, normally, readily identify logically appropriate verb sets for category and/or category sets for a verb set that are logically likely and/or sensible options, and similarly through such an arrangement, some embodiments may interpret and provide constrained options of adverbs, prepositions, and/or adjectives, given specified categories, verbs, and/or Core Purpose and/or other purpose expression sets.
In some embodiments Master Dimension Facets describe primary purpose properties normally used as approximate characterizations which, when used in combination with Core Purpose, may substantially illuminate the context of a specified or inferred prescriptive, and similarly inform descriptive, Core Purpose Expression. The following are Master Dimension Facets as may appear in some embodiments using some or all of the faceting options discussed herein:
User Facets may include, for example:
a. user sophistication/expertise related to Core Purpose, such as beginner/middling/advanced/expert;
b. user Role, such as member/participant/administrator/executive/head/decision maker/student/teacher/relative/spouse/sibling;
c. user focus, such as simple/middling/complex/narrow/medium/broad/local regional/global/universal/small/moderate/large/Quality to Purpose/Quality to Value/Quality of Publisher/Quality of Creator/Quality of Provider/Point-Counterpoint;
d. user viewpoint, for example, negative/neutral/positive/unassertive/neutral/assertive/uncertain/inquisitive/c e rtain/concerned/unconcemed/cheap/reasonable/expensive (relative to subject);
e. user experience (subjective feeling), such as stimulating/exciting/tranquil/happy/calm/unemotional/sad/challenging/undem anding/funny/irritating/

Resource Facets: In some embodiments describe characteristics of published resource instances and Classes, the foregoing for approximation expression purposes:
a. short/medium/long;
b. inexpensive/normal/expensive;
c. simple/intermediate/complex;
d. singular/compound;
e. current/recent/in between/old/ancient;
f. audio/video/printed/direct human;
g. electronic/mechanical;
information/process/software/hardware/firmware/service; and/or the like.
Repute Facets, which may be associated, singularly, or where appropriate in aggregate or combination, with any Cred type Repute, may include (where "or generally"
different, not mutually exclusive, separate Facet), for example:
a. Quality to Purpose ¨ e.g. numeric value -10 to +10 b. Quality to Value c. Quality to Contribution to Purpose d. Quality of Publisher to Purpose (or generally) e. Quality of Creator to Purpose (or generally) f. Quality of Provider (e.g. reseller) to purpose (or generally) g. Integrity of Creator (general or to purpose) h. Integrity of Publisher (general or to purpose) i. Integrity of Provider (general or to purpose) j. Reliability to Purpose (general or to purpose) In some embodiments, the foregoing Facet examples might be available in any combination, with or without variations in labeling or type. Such Facets may be organized as generalization approximation characterizations of key user/Participant concept sets, such as organized in a standardized expression and interpretation manner and may be further organized in focal logical groupings corresponding to human general and/or Domain general, key attributes, and employed in specification to, for example, provide input into identification, filtering, evaluation, prioritization, selection, provisioning and usage of resource and resource portion sets.
In some embodiments, PERCos published resource items may have four basic information types, resource identifier, publisher (which may have a unique identifier), subject matter, and at least one purpose expression, and may further have complementary types, such as creator, provider, contributor, ontological and/or complementary taxonomic information, and/or the like, as may be specified in some embodiments and/or specified by affinity groups, corporations, societal organizations, standards bodies, and/or the like.
In some embodiments, purpose expression specifications may use, for example, Domain category instances that may be used with, for example, clarifying prepositions, including adposition sets, positions and/or durations in time or location, and/or adjectives such as colors, size, emotional attributes, and/or the like as various embodiments may provide. Standardized Master Dimension Facet and/or other Dimension lexicons may be further constrained in some embodiments by selected verb, Domain category, and/or Core Purpose sets specified or otherwise selected by user set and/or user computing arrangement as a constrained set offering the logically associated optional contextual simplification variables for a given selection set (e.g.
one or more previous selections). Users may define their own simplification sets that may employ their own choice list synonym, relational association, word/phrase, and/or like lists for customizing their own, or groups, purposes.

In some embodiments, one or more verbs can be associated with one or more Domain categories as descriptive Core Purposes in CPEs declared as descriptive of purpose class applications (and/or other resources) by one or more Stakeholders. Users may select such a characterized resource set by selecting an icon or some other symbolic representation of such resource set where a symbol, for example, was published by a Stakeholder, e.g., a resource publisher, or by a user set, as a branding, purpose characterizing, and/or other identifying representation. Users may also publish for their own use (and/or may publish as Stakeholders) Frameworks, purpose applications, Foundations, resonances, CPEs, and/or other Constructs and associate any one or more of such Constructs with representative symbols. By selecting such resource set, a user may be specifying one or more Core Purpose and/or other CPE combinations, which such selection may produce, that is extract or otherwise transform to a purpose specification set that may be derived from other PERCos environment information and employed as input to other user purpose operations.
In some embodiments users may arrange information of their choosing (subject to context and any associated rights) into purpose expression organizations, for example as classes, ontologies, taxonomies, and/or the like. Should a user wish to publish such organizations there may be one or more formalisms that are applied during publication to ensure standardization and/or interoperability for the wider and/or intended audience.
Experts may use standardized and/or interoperable purpose expression organizations for their information, such that they for example, conform to the specifications agreed with a domain of expertise, interoperate with one or more purpose applications, may be appropriately interpreted by one or more intended users, and/or in other manners provide an effective and efficient organization for purpose operations.

A user purpose expression represents "the tip of an iceberg", the visible portion of complex set of human behavioral and thought processes. The orientation of purpose may evolve during purpose processing and may occur across portions of one or more PERCos sessions. User understanding of purpose is often constrained by the degree of expertise a user has relative to their purpose expression (and the Domain set of that purpose). During one or more sessions, a user's purpose may increasingly be represented by, due to the unfolding set of processes, an increasingly optimized purpose expression that is a more accurate or more satisfying, evolving representation of users' intent development.
An external resource service, such as a PERCos embodiments synonym service, may be invoked by other PERCos embodiments resources, such as Coherence, and may provide options and/optimizations to users, such as for example when CPE comprises "booking"
(verb) and "Travel" (category), PERCos embodiments may prompt "Purchase" to user in substitution of "Booking".
In some PERCos embodiments, lexicons can comprise the terms most commonly used in the identification of purpose experiences, and in common with other PERCos embodiments languages, provide standardized and interoperable means for users to manage, discover, select, and/or otherwise manipulate and/or inspect for later use, appropriate experiences and their resource (e.g. Participant, content instance, and/or the like), purpose expression, nodal arrangement information such as location, computing resources, and/or the like.
Purpose class applications, in some embodiments, provide significant capabilities for users to realize their purposes. Purpose class applications are resources that comprise a resource set that has been specifically arranged to provide a user computing environment for a specific, logically related set of purpose Outcomes. Users may employ a purpose class application with the specific understanding that they were constructed to provide specifically targeted (to one or more purpose expressions) sets of capabilities that may have particular, expert and/or otherwise fashioned features, such as software application interface (such as faceting engine), display, communications (for example, cross-Edge), expert system and Al support capabilities, all in a mutually complementary, multi-featured milieu specific to one or more class, hierarchical, ontological, and/or other logical and/or relational (for example human associated) based organization of capabilities as specified in the context of a purpose expression set.
Purpose class applications may, in some embodiments, be used to populate user computing environment "desktops" with symbols corresponding to, and, in some embodiments, in part or whole incorporating, branding, purpose class, publisher name, Outcome one or more facets, and/or the like so that initiating user computing arrangement purpose fulfillment activities brings the user directly into a resource environment for the corresponding purpose fulfillment specified class arrangement. PERCos capabilities may then be, in some embodiments, infused into the capabilities of the purpose class application, providing information resource and/or resource portion assistance, for example, for more granular, targeted, knowledge enhancement, and associated learning and discovery. With some embodiments, over time, and with the evolution of a PERCos Domain set specific or general cosmos, much of user activity may be "funneled"
by the user through purpose class applications, with PERCos capabilities serving the user in a more specific information, user purpose knowledge enhancement and/or decision making manner. For example, a purpose class application might comprise a "learning and practicing auto mechanics" environment populated, in part, with a spectrum of brand and/or model specific mechanics electronic manuals provided by experts and/or the respective manufacturing companies and/or associations thereof and/or the like, supported by logical, expert framed faceting capabilities for diagnosing problems and/or for choosing remedies, and further supporting a body of consulting experts available, for example, on request, and/or currently online, and/or, for example, further providing information regarding any associated consulting fees and/or other considerations, where such one or more consultants (e.g.
contingent on availability, scheduling, and the like) may, for example, be called upon at a given point in a learning, diagnosing, and/or repair process, all the foregoing, in such example, may be supported by graphics capabilities that can "walk" a user set through diagnosing and/or servicing a vehicle mechanical problem, including learning support capabilities such as reference and diagnosis specialty information that may be contextual (at a process point) available, and/or graphical and/or video close-ups, for example on user request. These and other capabilities can create very powerful application sets populated by contributing resources (which may include in some embodiments one or more other resources not meeting the definition of a PERCos published resource), that may be evaluated and/or, custom employed, for example, in using a purpose class application allowing for selectable resources to perform one or more Roles contributing to the applications resource array. Users may further "build" purpose class applications, for example, by working with a Framework that is associated with the user purpose "learning and practicing auto mechanics" which may provide a scaffolding, including, for example, a portion of useful resources (which may include in some embodiments one or more other resources not meeting the definition of a resource).
In some embodiments, purpose profiles may be used by both users/Stakeholder to store those characteristics they wish to associate with one or more purpose(s) and/or purpose ontological and/or taxonomic groups, including, for example, purpose classes. For example an expert who has multiple domains of expertise, potentially with differing skills levels in each may develop a purpose profile associated with one or more Domains. In addition, one or more users/Stakeholders may also have purpose profiles that are optimized to their own specific stored purposes (as, for example, CPEs).
A PERCos web service arrangement may maintain participant characteristics, e.g. profile information, as associated with any purpose ontological and/or taxonomic arrangements, such that based on one or more characteristics associated with a specified purpose set, e.g. a purpose expression, associated one or more parties could be identified and prioritized, for example, as further assessed according to Creds on their characteristic qualities/capabilities (as well, for example, on EFs, such as descriptive participant professional attributes).
In some embodiments, such purpose profile formulations may be associated with and/or potentially be part of preferences, and may in part or in whole form the context for the intended and subsequent purpose operations.
In some embodiments, users may for example, choose a purpose profile from one or more Experts, Stakeholders, other users and/or social networks with which to undertake, for example, collaborate and/or share, their purpose fulfillment operations.
A Few Further Examples For example a user group may be trying to repair a bicycle, car, electronic device and/or the like.
As they undertake their purpose operations, for example as they try to diagnose the problem, users may experience an evolving of understanding of the components and related issues that make up the devices and the match of symptoms to problems, for example, through the direct and/or indirect assistance of others who have experienced these issues and/or have material issues related expertise. This may lead for example to an expert and their published resources and/or online, real-time assistance, which may provide an informing context leading to appropriate remedial actions that satisfy a user purpose set.

For example, in some embodiments, user (U1) may express (PE1) which through use of class systems and PERCos embodiment processing, may result in a set of resources ( RS1) comprising some classes with a significant and/or sufficient correlation/relevance to PEI. For example RS1 may comprise classes Cl, C2 and C3. Each of these classes may have as members resources, expressed as C1(r11...m1), C2(r21, ..., rn2), and C3(r31, ..., m3), respectively.
In this example, user Ul has experience of RS1 and selects member of RS1, R(x), to be part of their iterated purpose expression. In some examples this may lead to creation of a new purpose expression, PE2, where none of the terms of PE1 are retained in PE2 or a revised PE, where some of the terms and/or expression combinations of PEI, for example designated as PE1(a), are retained. For example if PE1 comprised CPE(Learn, Solar Cells), then PE2 may comprise, for example CPE(Purchase, Solar Panels) or PE1(a) may comprise CPE(Learn, Solar Panels).
In this example Ul may elect to retain each PE and associated result set, so that they may traverse their "tree of understanding", enabling them to consider differing selections and digressions as they, through experience of considerations and evaluations of RS develop further understanding of their purpose Domain.
This may include retention (through, for example, one or more storage means) by Ul and/or those resources associated with Ul purpose operations, the relationship information and/or result set, including the selections and decision trees of Ul.

When a user expresses a purpose expression for which PERCos does not have sufficiently clear information, PERCos may evaluate the purpose expression to find a set of purpose expressions that are as "near" as possible. Consider Figure 1, some purpose Domains share some common purposes, whereas other purpose Domains do not share any common purpose. A
user may specify a purpose expression that generalizes to a purpose class in purpose Domain PD3. Further suppose that there is no descriptive CPE associated with a PD3. In such a case, PERCos may consider PD1 and PD2.
An illustrative example of purpose Domains with common members is shown in Figure 1.
In some embodiments, purpose Domains are a special type of class that are focused on purposes.
In some embodiments, purpose Domains nomenclature may be standardized and may be aligned with one or more class systems. Such standardization may include for example descriptive CPEs which may be associated with purpose Domains.
In some embodiments, there may be associated tables comprising one or more purpose expressions, such as verbs and categories, which represent associations of one or more purpose Domains with other resources and/or resource portions, including purpose Domains. For example this may include verbs, categories, CPE and/or other purpose expressions and/or metrics (such as for example weightings) indicating the relative strength, closeness, nearness, co-occurrence, frequency of occurrence and/or any other metrics.
In some embodiments such tables and the values they comprise may be used by PERCos embodiments' purpose operations to determine relative utility of those resources.

In some embodiments there may be additional purpose expressions associated with purpose Domains, for example in some embodiments, this may include PIDMX which may comprise all the purpose expressions with which purpose Domain has been associated and the relationships between purpose Domain (as a resource) and other purpose Domains (as resources).
For example PD1 may have associated descriptive CPE [Learn Math] as this PD is a resource for learning general math. In some embodiments, PD1 may often be used by multiple users in conjunction with PD2 which has descriptive CPE [Learn Physics] and consequently, for example, each PD PIDMX may have this relationship enumerated so that PD1 and PD2 may, in some evaluations be determined to be close/near.
In some embodiments, provisioning of a user purpose may take into account factors such as for example, the user's postulates, one or more stored profiles, preferences, contexts, such as the user's expertise in the purpose domain, and/or the like. For example, suppose a user is interested in exploring investment strategies. Figure 2 illustrates the user having three sets of decision points. First decision point may be to specify the user's "what if Postulates," such as the user supposing what happens if Greece will default and the stock market will go down as a result.
The second column of decision points may be the user exploring the user's expertise level, such as supposing the user is an expert investor, knowledgeable investor, beginning investor, and/or the like. The third column of decision points may be to explore different types of investment strategies. Based on the cumulative decisions, PERCos can, for example, interact with one or more resource knowledge bases to generate a list of resources employed to fulfill user's purpose.
An illustrative example of a user's resource selection is shown in Figure 2 In some embodiments, users may have interactions involving their beliefs, for example as expressed as user specified constraints on purpose operations and/or as constraints included in their evaluation operations on results sets created through purpose operations.
In some PERCos embodiments, user experience and discovery are reflected in user horizons as they adjust over time and process events, including interaction and experience events during their pursuit of purpose.
Unfolding management, in some PERCos embodiments, comprises cross Edge management where user outputs direct the potential results sets that may satisfy their dynamically unfolding purpose operations during one or more iterations of purpose expressions.
Users may also have multiple iterative purpose expressions reflecting users developing understanding within their purpose operations.
In some embodiments, purpose expressions may be processed, in whole or in part, through PERCos embodiment processes. These processes may include operations and/or processing of purpose expressions that for example, include:
= Delayed processing of purpose expressions- Where for example, users and/or other process input may invoke one or more various delays in purpose processing, to for example take advantage of differing resources, match processing to resource availability, synchronize with other users, conform to specifications (for example rules) determining the time periods for such operations and/or the like.

= Intensive processing (using multiple resources including for example Cloud based resources) - where for example the use of more powerful, capable and/or sophisticated resources may compliment and/or further enhance user resources for further/additional processing capabilities.
= Specialist Processing ¨where for example, use of specialist processing tools, such as computational linguistic, semantic and/or other analysis tools, which may be operated within user's resource pool and/or in cloud.
= Simple/Quick/Instant processing/responses- where for example pre calculated and/or indexed purpose results sets where expedience is the priority.
= Quantization of processing (delivery of results in "chunks", including accretive/iterative)-where for example, purpose results sets are provided in quantized "chunks", for example results from one category, results from one resource, results that satisfy a specification and/or the like.
= Collaborative processing- where for example a set of users utilize their specific resources in pursuit of their common purpose.
In some embodiments, these arrangements of resources may be made persistent and/or published, often in line with PERCos embodiments Constructs as Foundations, Frameworks, and/or the like.
In some embodiments, user's initial purpose expression(s) may be processed and subsequently retained over time for further periodic processing. This may include processing and purpose results sets that are built up over time, which for example may include the creation and/or iteration of associated classes and/or other organizational structures.

Such contiguous, sequential, periodic and/or other temporal purpose expression processing may include specification of purpose expression lifespan, for example quantized by user/Stakeholders based on metrics that may include for example, utility/time/cost/sufficiency/group dynamics and/or the like.
Users may elect to have their purpose operations produce results sets in any time frame (and/or series thereof). For example user may elect to have purpose operations deliver results sets immediately, as for example they may need such results to respond to a query at that point in time. However, users may also elect to have that results sets extended, expanded and/or modified over a time period, which for example may be set by user/Stakeholder over time, where further results may be composited into results sets for user.
In some embodiments, users purpose operations may include the utilization of one or more autonomous or semi-autonomous agents as resources that may represent users in the intranets, extranets, and/or the web and user purpose seeking agents may trawls resource space for appropriate resources selected by user as expressed in a purpose expression such as a CPE or Purpose Statement.
In some embodiments these resources may provide functionality that for example enables users to retrieve identify, select and/or retrieve resources for users controlling the agents. There may also be agent resources that represent the users (in whole or in part) and may provide interactive capabilities for other users (and or their resources).
In some embodiments, a user set may select one or more PERCos Repute categories from a list arrangement. Such category selecting, for example, may use a faceting interface. For example, a user may select as a desired attribute for a Cred set to be applied as associated with a user's Core Purpose, 'learn' 'molecular physics developments,' selecting from logically presented options of expert types in physics. For the above or other example, a user may select a desired authority certifying type for administering a certification, degree and/or other validation of a claim of a professional position, degree, and/or the like, as an Effective Fact:
licensing authority, board certifications, fellowship providing authority (e.g., Fulbright program), and/or the like;
academic/technical/professional degree types, such as an AA, BA or BS, Ph.D.
and/or the like;
memberships, such as ACM, IEEE, NRA, ACLU, and/or the like; employment position types, such as assistant professor, public middle school teacher, vice president, fireman, manager, director (title or board based), lieutenant, and/or the like; employment institution types such as university, college, corporation, non-profit, religious, consulting firm, government, and/or the like; employment institution ranking types such as nationally recognized, internationally recognized, regional, local, and/or the like; region of location such as global, specific hemisphere, continent, subcontinent (middle east, central America), nation, state/province, city;
asset status types of categories, and subcategories of available categories as practical and circumstantially appropriate. An IU can, in particular employ such category types when specifying Repute EFs and Creds for creating an expertise and/or otherwise appropriate informed and prioritized list of resource candidates for further evaluation and/or selection of and/or interaction.

Non-limiting Sample Embodiment of a General Purpose, Extended, Constrained Verb Set Variations on this embodiment may involve combining certain separate verbs as approximation.
Describe Assert Commit Explain Open Undo Instruct Store Enlarge Teach Influence Observe Learn Persuade Solve Study Argue/Dispute Enhance/Supplement/Add Research Annoy/Irritate Give Ask Avoid Receive Refuse Disrupt Withhold/Keep Analyze Locate Plan/Design Explore Publish Forgive Discuss Acquire/Get Remodel Entertain Compare Reply experience Place/Put Send Contemplate Attack/Fight Remonstrate/Disapprove Criticize Enjoy Operate Contribute Ignore Execute/Process Create Support Restore Debate Defend Move Purchase Make/Assemble/Produce Sense (touch, smell, taste, hear, feel) (multiple) Administer Fix/Repair Want (To Enjoy, To Move, To Share Grow feel, To Play, to Pursue and the like) Communicate Complete Play Socialize Inspect Meet Reduce/attenuate Pray Possible Negatives such as lie, Compete Travel confuse, misdirect, harass, Resolve Consume Gift Interact Employ Yearn Negotiate Observe Delete/Remove/Eliminate Combine Participate/Attend Manufacture Select/Choose Belong/Join Maintain Close Contest Stop Modify Oppose Dismantle Complain Sell Disable 1 Introduction ¨ Resources In one aspect, PERCos embodiments view computer operations as involving a simple duality:
the interaction between users and computer processing arrangements. Users are able to contextually, relationally compute and respond (human thinking and action), for example, in a form that reflects approximation thinking. Computers involve a rather different class of digital and analog processes and supporting elements.
PERCos embodiments arrange the totality of resources supporting computer users in a manner that is responsive to human instructions. The PERCos resource architecture provides computational components within this simple human/computer duality. It organizes a totality of resources as elements that can be selectively combined and arranged to fulfill user purpose(s), including providing purpose responsive human experience elements and/or other results.
PERCos resources may be provided in some embodiments, for example, in several different forms, for example: Formal resources, Implied resources, Ephemeral resources, and Compound resources (multiple of these forms may apply to a given resource instance and/or resource class, either as to one or more parts and/or as to the whole):
A Formal resource is, at minimum, comprised of (a) a persistent, operatively unique identity (e.g. should not be ephemeral or intentionally temporary and unreliable as an identifier, along with any enforcement of this criteria depending upon the embodiment), (b) a subject matter that is the processing and/or processable material (including, for example, a human Participant descriptive information, and which may, for example, include how to initiate contact, or use, a Participant, for example, as a resource), (c) a formal publisher set (named, or otherwise identified as may satisfy a rule set, including having a persistent, operatively unique, identifier, for example, as above) for such resource, and (d) at least one associated and context providing purpose expression such as a CPE, except in embodiments employing at least in part Core Focus instead of a purpose expression set. Such resources are interpretable by at least one or more PERCos embodiments, and their subject matter may or may not be useable, depending on the presence or absence of necessary other resources and/or conditions. SuchFormal resources may contain or otherwise reference other descriptive metadata, such as author, provider, language, interface, user and/or other participant set usage history (for example generally and/or as associated to one or more purpose expression, participant, association with other resources/resources, sets), and/or any Repute information as described as a capability of a PERCos embodiment, or, for example of publisher, creator, provider and/or the like sets, for example, including associated use of Effective Fact (EF) and/or Faith Fact (FF) sets. See figure a, a sample embodiment (that is, non-limiting) of PERCos Formal resource element information types. Formal resources are published, including registered, through use of an identity schema arrangement supporting plural, independent parties as publishers, wherein such schema arrangement provides information constituting and/or is otherwise employed as at least a portion of a persistent, operatively unique identity for such resource. Such registration schema may be at least in part managed, hosted, and/or otherwise controlled by, one or more cloud services and/or standards organizations. Such one or more services and/or organizations may accept at least a portion of such identity information or input thereon from such resource publisher set and/or another party set(s), wherein such information may supplement, complement, and/or otherwise contribute to such identity information.
An Informal resource is, at minimum, comprised of (a) a persistent, operatively unique, identity (e.g. should not be ephemeral or intentionally temporary and unreliable as an identity), (b) a subject matter that is the processing and/or processable substance of the resource (including, for example, a Word Processor such as Microsoft Word, that can be employed in creating and editing documents), (c) an implied resource publisher -- this may be an interpreted or otherwise inferred originating publisher of such resource, or this may be, for example, a different Stakeholder type such as a Participant provided and caused to be stored preference information indicating choice of Microsoft Word as word processor, or when a Repute Cred asserter -- or if sufficient information exists -- a Repute EF declarer stipulates that Microsoft Word is a word processor) or when a user stipulates, or a user PERCos Foundation has been employing, a local version of Microsoft Word as a word processor, and (d) at least one purpose expression associated with such subject matter as specified by such implied resource publisher either directly by such publisher, and/or indirectly by a resource Creator and/or other Stakeholder set.
Such informal resources may contain or otherwise reference other descriptive metadata, such as author, provider, language, interface, user and/or other participant set usage history (for example generally and/or as associated to one or more purpose expressions, Participants, association with other resource sets), and/or any Repute information as described as a capability of a PERCos embodiment, or, for example of publisher, creator, provider and/or the like sets, for example, including associated use of EF and/or FF sets. Informal resources are published, including registered, through use of an identity schema arrangement supporting plural, independent parties as publishers, wherein such schema arrangement provides information constituting and/or is otherwise employed as at least a portion of a persistent, operatively unique identity for such resource. Such registration schema may be at least in part managed, hosted, and/or otherwise controlled by, one or more cloud services and/or standards organizations. Such one or more services and/or organizations may accept at least a portion of such identity information or input thereon from such resource publisher set and/or another party set(s), wherein such information may supplement, complement, and/or otherwise contribute to such identity information.
An eEphemeral resource can be, at minimum, comprised of a non-persistent subject matter that is a separately identifiable processing and/or processable substance arrangement that is dynamically produced, provisioned, and then no longer maintained, or not maintained beyond a short, session operatively appropriate time frame.
Compound resources have all the characteristics of formal and/or informal resources, but are further comprised of a plurality of formal and/or informal resources. Compound resources may also, respectively, be formal (if all compounding resources are formal), or informal (if not all compounding resources are formal).
Formal, Informal and Compound PERCos resources are persistently associated with at least one identity, where an identity is operatively associated with at least one resource interface arrangement. A resource interface arrangement can provide sufficient information to validly invoke operatively associated methods of a resource instance. Common kinds of values that may be named include data/contents, and/or specifications for such data/contents, hardware, devices, processes, software/applications, and/or networks. PERCos resources are identifiable elements within, or accessible to, a PERCos system that may directly participate in computer processing operations, including data, software, a service, firmware, hardware, a device, a Participant, and/or a combination of the foregoing resources in PERCos arrangements. PERCos resources may be organized, managed, and/or deployed through the use of purpose, resource element (e.g., purpose class applications and other Frameworks, Foundations, Domain related and/or the like), and Participant ontologies and class structures, facilitated by other information, such as metadata and/or purpose expressions that may be associated with PERCos elements.
Figure h illustrates an example embodiment of contributing and operative resources.
A PERCos embodiment can be a network operating environment which enables purposeful computing, extending traditional operating system capabilities by uniquely enabling user expressions of purpose, and further employing apparatus and methods to optimally match user Contextual Purpose Expressions (CPEs)¨and any associated specifications (including user and Stakeholder preferences and/or rules), metadata and/or Foundations, and/or the like ¨to resources available and/or on one or more networks. A PERCos system embodiment is designed to support the deployment of resources to provide user experiences that are responsive to user purposes.
With PERCos embodiments, users can intelligently and efficiently interact with a global, nearly boundless "purposeful network," comprising an immense diversity of possible resources that are aggregatable and configurable as purpose-responsive arrangements. A feature of some PERCos systems is their organization, and management of potentially actively contributing elements of a session as components of a logically unified resource infrastructure.
Processing elements, any and all contributing forms of information, any and all contributing forms of network resources, device arrangements, Participants, and/or the like can be uniformly treated as resources.
Resources may be aggregated, and are identifiable, assessable, and deployable in response to user purposes, subject to specification and other operational context.
Computer memory, devices, microprocessors, databases, software, services, networks, Participants, and other specification types may be managed by PERCos Resource Managers.
In some PERCos embodiments, management of resources is separated from the resources themselves, with both resource managers and resources being able to be arranged in any manner to suit purpose operations. These distinct arrangements of resources and resource managers are combined into operating fabrics, providing dynamically flexible support for unfolding purpose operations.

Purpose specifications serve basic functional roles in the information management of resources within PERCos. Operating systems traditionally supply applications that are suitable for pre-identified general activity types (word processing, spread sheet, accounting presentation, email, and the like). A PERCos system embodiment, in contrast, is designed to supply experiences and results corresponding to expressed purpose specifications by providing resource arrangements whose unfolding executions are specifically in response to purpose specifications.
To minimize the level of effort users need to expend to formulate optimal purpose specifications, a PERCos system embodiment may provide a range of Constructs, specifications, services, tools, and/or utilities. These may include, for example:
A suite of identity management services to enable resource discovery, evaluation, selection, and/or assembly to be undertaken efficiently without necessarily directly manipulating underlying resources.
A suite of information management services configured to discover, extract, and/or manipulate useful purpose-specific information from huge arrays of data that have been captured and published as resources.
A suite of other platform services and utilities, such as registration/publishing, resource information matrix, commercial flow management, and Repute services to identify candidate resources in fulfillment of Contextual Purpose Expressions.
Resource arrangements that may include Constructs of varying granularities that enable one or more users, and/or systems to develop, identify, and/or prioritize rich, nuanced, and highly-responsive purpose operations leading to user purpose satisfaction through purpose experiences.
A suite of Coherence Services that may detect and/or attempt to rectify a wide range of limitations, imperfections, and/or exceptions, including, for example, inaccuracy, lack of clarity, incompleteness, inconsistency, inefficiency, suboptimal selections, and/or requests for unavailable resources.

A suite of Repute and resonance services to support optimization as to quality of purpose and purpose resource alignment for purpose Satisfaction. These services may lead to superior purpose experiences that integrate the interests ofStakeholders.
A PERCos system embodiment takes purpose specifications and ascertains their validity to identify optimal arrangements of resources whose unfolding execution may provide experience and/or results that correspond to purpose specifications. Initially candidate specifications may possibly be incomplete and/or describe resources in abstract/general terms and/or contextually.
In such an embodiment PERCos embodiments processing may evaluate, align, resolve, cohere, refine, filter, prioritize and/or otherwise operatively manipulate resources and their specifications (including any associated information sets)to ascertain the validity of such purpose specifications. In some embodiments, a PERCos system may use Coherence Services to validate purpose specifications.
A PERCos system embodiment may also check the availability of the identified resources. For example, such embodiments may check that a user has sufficient authorization to access one or more resources and that such resources are not already operatively committed by one or more conflicting uses. If appropriate, Coherence processes may interact with the user and/or Stakeholders for clarification and/or elaboration. For example, suppose that the user is not authorized to access some resource, and Coherence cannot find an alternative or substitute resource. In this case, the embodiment may then request the user and/or Stakeholders for further guidance.
A PERCos system embodiment may take a resolved and cohered purpose specification, allocate those resources that are available, and request reservations for the rest (for example through PERCos resource reservation systems described in this disclosure). In some embodiments, a PERCos system may also generate operational specifications that have sufficient resource specifications and instances to support an operating session that corresponds to the purpose specifications. Some purpose specifications may require a given level of performance and reliability; some others may require a high degree of security and/or privacy.
In some embodiments, a generated operational specification may comprise resource arrangements, such as Frameworks, resource assemblies, resource Foundations and/or other aggregations of resources that have previously been created and utilized.
Resource arrangements, together with suitable methods for accessing them (e.g., getting, setting, and modifying their values) may be used to construct "more abstract" resources and manage them. Thus, resources may be dynamically assembled into new resources for inspection, analysis, selection, and/or deployment purposes.
This disclosure describes a PERCos Resource Management Systems (PRMS) that may be used in some embodiments of PERCos systems. A PRMS embodiment is configured to provide and manage arrangements of resources in accordance with Contextual Purpose Expressions and other PERCos information arrangements so that users may experience, store, and/or publish computer sessions and/or session elements that provide the best fit to their Purpose Statements.
PRMS embodiments provide a highly scalable and extensible resource architecture that allows PERCos systems to manage all types of resources, regardless of their size, complexity, diversity, location, format, and/or methods of creation and to treat them uniformly. Such a PERCos resource architecture enables PRMS to uniformly organize and process databases, computational processes, networks, Participants and specifications, including providing common service and/or resource management interfaces for individual and/or aggregations of resources.
A PERCos resource architecture embodiment also enables aggregations of resources to be arranged and combined with a resource interface to create a composite resource. Composite resources, in turn, may be arranged with other resources and resource interface to create even more capable composite resources, ad infinitum. This enables users and/or Stakeholders to create and use resources at any chosen level of granularity.
A PERCos embodiment may include a PERCos Information Management System (PIMS) that may enable users (novice or expert) and/or other stakeholders to describe, capture, and organize information about resources, including metadata. A PIMS embodiment can be comprehensively extensible in its ability to represent created resources. Organizing resource information through the use of PIMS enables resources for user purposes to be discovered and managed more efficiently than in existing forms of resource organization, management, and identification, which do not directly support user purposes. PIMS enables resource-related information to be organized in correspondence with CPE expressions and/or elements, regardless of their location.
This allows users' Purpose Statements to be provisioned optimally without arbitrary constraints on the location or publisher of the resources used.
PRMS embodiments accept operational specifications that request levels of service from classes of resources. Such an embodiment checks accessible resources to determine the most suitable arrangement of available resources. In some embodiments, PRMS may use Coherence Services, to harmonize the operational specification with the accessible resources.
Based on its determination, the embodiment may negotiate and establish one or more operating agreements that specify resource provisioning, including levels of services and/or methods to be supplied by each resource. Negotiated levels of service and methods may be explicitly specified by, and/or implicitly derived from, Purpose Statements, and may specify in some embodiments, for example, performance, functionality, reliability, redundancy, confidentiality, integrity, and/or other characteristics. PRMS embodiments may then manage and monitor the performance of resources to ensure their compliance with the negotiated operating agreements.
In the event one or more resources fail to perform, PRMS embodiments may take appropriate actions, for example, executing corrective measures (e.g., replacing failing resource(s), adapting to event based circumstances), notifying and/or requesting action from appropriate processes, users, and/or other stakeholders.
PRMS Reservation Services, in collaboration with PIMS and/or PERCos Platform Persistence Services, enables the scheduling of resources, regardless of whether they are active, inactive, disconnected, or unavailable. PRMS Reservation Services also allow resource metadata to be persistently available for resources that may not be currently available for use. PERCos processes and/or services may use this same capability to resume their processing after pausing, and for example, using the PERCos Platform Services to persist part or all of their operating states, in a manner suitable for resumption and/or other processing.

PRMS embodiments may also allow users to reserve resources¨ for example, resource sets in the form of Frameworks and/or Foundations¨that may not be operating and/or available at the time of reservation. Users may benefit from reconfiguration of their Foundation resources. For example, a user may have one or more mobile devices as part-time elements of a Foundation-for periods of time, they may be inactive or disconnected. A user may arrange to reconnect disconnected mobile device(s) with minimal interruption to their operating experience, by reserving the mobile device(s) in advance. For example, if a user might use PERCos embodiment on an office desktop to obtain a contextual purpose experience, then leave the office and still continue to obtain the experience, without interruption, on a reserved mobile device.
PRMS may provide mechanisms for recording resource-related information, which includes those resources with which a resource has interacted and may include information such as performance, component configurations, activities, statistics, operational results, and purpose, class, and performance metrics. This information may, in whole or in part be based on the resource's recording specification.
Some PRMS embodiments may enable resources to have associated Repute information about themselves and/or other resources with which they interact. For example, this may include assertions regarding some or all of a resource's performance, security, reliability and/or other operating characteristics, Repute information regarding CPEs, and/or the degree to which resources contributed to purpose satisfaction.
In some PERCos embodiments, a resource may comprise one or more identifiable elements that may be employed, or otherwise directly participate, in PERCos computer processing operations.
Resources can include what are commonly called "information resources,"
"computational resources," "communication resources," as well as computer representations of users and their actions. Any specifically identifiable element whether locally known or unknown can be made into a PERCos resource. Such an element may be (or refers to) any process or item, internal or external, and/or any algorithmic combination thereof. Common resource embodiments are specifications of content, hardware, devices, software, services, Participants, networks, and/or arrangements of the foregoing. PERCos embodiments flexibly support the organization, Provisioning, and purpose-related Governance of a potentially boundless collection of possible resources, often with the goal of achieving optimal responses or response candidates to purpose specifications.
In some PERCos embodiments, a resource has a persistently associated identifier and at least one resource interface. Common kinds of resources include specifications of content, hardware, devices, software, services, and/or networks.
The information in a PERCos system embodiment is accessed, processed, and stored by resources. Ultimately, resources are about the results of information and/or information handling and/or processing: its generation, representation, storage, retrieval, consequences, and the like.
Except at the user interface, users need not perceive the physical apparatus and method embodiments and processes involved in a PERCos system, only that appropriate inputs lead to corresponding outputs, with (if applicable) a stated degree of trustworthiness/security/reliability and/or other result.
In some embodiments, a PERCos resource interface (PRi) may provide sufficient information to validly invoke methods of a resource instance. Resource interfaces may include organizational, control and/or interface (including communication protocols) specifications and access to its method specifications and instances.
Resource interfaces may be standardized and interoperable, for example providing standardized interfaces for resource Roles.
Resources may request operations of other resources by invoking method embodiments available through their resource interfaces. This enables resources to interact with each other in an "information handling ecology."
In some embodiments, resource interfaces may include one or more sets of specifications, including:

= Control specifications specify operations of resources that are combined into a Construct and may include, for example, purpose operations specifications, navigation and exploration control specifications, and/or purpose formulation control specifications.
They may be used in the control and management of varying, and potentially very large, resource arrangements.
= Organizational specifications specify organization and arrangement of resource elements that comprise such resource and those organizational relationships of that resource with other resources. For example this may include organizational specifications that may include specifications for one or more purpose organizations.
= Interface specifications specify interface characteristics that may be accessed and/or interacted with by other resources, such as resource Roles. In some embodiments these may be standardized PERCos resource interfaces with associated interface specification sets, and may include operating agreement specifications, which express and determine interactions between a Construct and other resources and/or interactions among resources comprising the Construct.
Additionally there may be further specifications, including identity and resource characteristics specifications which are available (in part or in whole) to other resources, subject to agreed terms of interaction between the resources.
Resources may be comprised of any number of resources and/or resource elements. Conversely, a resource may be an element of any number of other resources, including, for example, resource assemblies, Constructs and/or other resource arrangements. As instances, they may be dynamic and have resources added, removed, and/or replaced.
As is described below, in some embodiments, resources may be arranged into PERCos Constructs.
A resource's behavior is characterized by its resource interface, and may be further enhanced and modified by further relevant specifications. This may include for example PERCos resource characteristics specifications, contextual purpose specifications, control specifications, Coherence specifications, resonance specifications and/or any other specifications. These specifications may be persistently or dynamically associated with resources.
For example, a resource may be characterized by a descriptive CPE, which has been provided by, for example, a resource publisher. Such embodiments may then be further modified by resource interface(s) and/or relevant specifications. Elements of a resource interface embodiment may be embedded in and/or referenced by resource metadata, and/or determined by applicable specifications.
In some embodiments, the resource interface determines to what degree, if any, access and/or interaction may be undertaken with the component suite instance of that PERCos resource interface.
For example, in figure 3, an illustrative example of resource interface.
PERCos resources comprise at least one resource interface and, in some embodiments, may include one or more elements. An element is an operational unit that is identifiable within PERCos. An element may or may not be a resource. Elements of resources may, for example, include one or more specifications, other resources and/or processes.
In some embodiments, there can be opaque resources and transparent resources.
Opaque resources are resources in which their respective resource interfaces do not provide any methods for direct access to the underlying component resources. A transparent resource has one or more methods that provide direct access to resources and/or resource elements comprising that resource. Between these two extremes is a translucent resource, which has one or more methods for accessing some resource elements comprising the resource but these methods are filtered by the resource.
For example, a particular PERCos embodiment might have a purpose class application resource that helps a user select a resource that may best serve the user's purpose.
The resource elements of this purpose class application might be several different resources that meet the purpose associated with the purpose class application in different ways. The purpose class application may have an interface that may guide a user to select and use the best resource for his particular purpose. However, if the user already knows which of the component resources best meets his purpose the purpose class application also has interfaces that allow the user to directly interact with the resource element of his choice.
For example, as illustrated in figure 4 an example resource with opaque resource interface (e.g.
Laptop Computer) is shown.
For example, as illustrated in figure 5 an example resource with transparent resource interface is shown.
A resource may also participate in the resource element suite of one or more other resources (e.g., a single disk may provide multiple partitions; a single processor may run multiple services.).
When a resource is invoked, via its resource interface, it is not relevant to the invoking resource and/or process how the results are obtained¨that is internal to the invoked resource. The invoker needs to know only that results are in accordance with the resource interface specification.
Common types of resources include CPEs, specifications, processes/services, Participants, data/content, hardware, devices, software/applications, communications media (such as a 1 mbit pipe) and/or any other PERCos expressions, and/or any other non-PERCos logical and/or physical elements, and the like.
In certain embodiments, resources comprise or otherwise reference resource interface and resource elements. Resource elements may comprise PERCos resources (PR) and non-PERCos resources (NPR). Non-PERCos resources are resources that are not PERCos compliant.
Frequently, an arrangement of resources (and/or identifiers (e.g. UIDs) designating resources) is used to form one or more resource elements that comprise part of a higher-level resource.

In some embodiments, PERCos may interact with non-PERCos resources, when, for example, a PERCos resource interface is instantiated. This may occur through, for example, the use of a specialist resource type known as an assimilator utilizing an NPR specific method set known as a transformer.
PERCos resource interface embodiments may also be created by PERCos resources, to manage their interactions with non-PERCos resources. The degree to which PERCos Resource Interfaces (PRI) integrate with non-PERCos resources may be chosen by PERCos. In some embodiments, a PERCos resource may interact with non-PERCos resources, subject to appropriate communications being established, directly and/or through PERCos resource interface.
For example, as illustrated in figure 6, an example of an (NPR) interaction through PERCos Resource Interface (PRI) is shown.
In figure 6, the Participant may interact directly through invocation of an appropriate communications protocol and associated method(s) (in this example the HyperText Transfer protocol (HTTP) and a Browser) with a non-PERCos resource and/or may utilize the PERCos resource interface for that interaction. In either case, the non-PERCos resource interacts with PERCos only through its own communications capabilities.
If a PERCos resource uses the PERCos resource interface with a non-PERCos resource, then the PERCos resource may gain aspects of the resource interface and treat the NPR
as if it were a PERCos resource. In one example, a PERCos resource tracks and manages all the interactions with a non-PERCos resource, such as a general purpose search engine like Google.com (GoogleTM is a Trademark of Google Inc.).
The degree of interaction may range from a simple identification of the NPR, through full integration with the PERCos resource interface.
Some PERCos embodiments may provide a selection of one or more APIs in any arrangement associated with, for example, one or more PERCos Platform Services. Such APIs may provide a developer, who may or may not be a user or Stakeholder of a PERCos embodiment, with apparatus and methods that may be used to, for example and without limitation, create, discover, modify, capture, publish, integrate, organize, aggregate, share and/or store elements of a PERCos embodiment, including, for example and without limitation, resources such as, for example, CPEs and other purpose expressions, Reputes, Constructs (such as, for example, Frameworks including purpose class applications, Foundations and/or the like), class systems, classes, and/or the like.
In some embodiments, developers may use PERCos APIs, for example and without limitation, for the development of = PERCos resources intended to be used in the context of a PERCos embodiment.
= Hybrid (PERCos-aware) resources may be able to function as PERCos resources in the presence of a PERCos embodiment but are able to function when a PERCos embodiment is not available.
= Non-PERCos resources may be able to make use of PERCos capabilities provided by a PERCos API.
For example, a developer may find PERCos coherence capabilities useful for the development of a network monitoring and response system. As another example, a developer may make use of PERCos Repute capabilities to build a recommender system, which may operate independently of a PERCos embodiment.
PERCos Resource Management System (PRMS) embodiments provide a dynamic environment that manages specified sets of PERCos resources, in whole or in part, as part of one or more PERCos operations.
Resource managers negotiate with operating session managers and/or other authorized processes so as to create an operating agreement. Operating agreements define the levels of service that an operating session can and may be committed to provide. Resource managers may interact with their respective information management system, such as PERCos Information Management Systems (PIMS) to obtain information on the specified resources, such as associated purpose expressions, publishers, Reputes, resource interfaces, functional capabilities, performance attributes, administrative requirements, control information, and/or the like, to assess its ability to monitor and comply with the requested levels of service. If a specified resource is a composite (i.e., an arrangement of resources), a resource manager may obtain information about the component resources that constitute the arranged resource. For example, suppose a laptop computer (for example a SonyTM VGN-Z520 computer) may be an example of a composite resource. In such a case, a resource manager may obtain information about the component resources of the laptop computer, such as its NVIDIA driver, to determine whether or not the resource manager can provide the desired level of video image processing.
Resource manager embodiments are responsible for managing their respective set of resources to ensure that they satisfy their respective operating agreement(s). As with resource provisioning, resource managers may perform the management task in a recursive manner. A
top level resource manager may divide the provisioned resources into a group of smaller "resources" and delegate the management of each group to a lower level resource manager instance.
Each resource manager instance, accepting the management task, monitors those resources under its responsibility. If a resource faults for whatever reason, the resource manager instance determines and performs the corrective actions, such as finding replacement resources and/or notifying appropriate process.
PERCos Resource Manager Services (PRMS) may use a range of methods to satisfy an operational specification. One method, for example, is to split the operational specification into a set of "smaller" operational specifications in such a manner that the set of sub-operational specifications collectively produce the same purpose results as the original operational specification. Another method is to provision the specified resources in a recursive manner.
A top level resource manager instance, receiving an operational specification, selects the method based on factors such as the location of specified resources, levels of services that may be required for each specified resource, and the size of the resource set. For example, suppose the specified resources are from multiple organizations and located across multiple networks.

Further suppose that the multiple organizations have widely different administrative requirements for the use of their respective resources. In such a case, the top level resource manager instance for example, may decide to delegate to lower level resource manager instances, one or more lower level resources to support each organizations administrative and/or operative requirements.
Part of delegation processing includes negotiating with a lower level resource manager a sub-operating agreement with which the lower level resource manager may comply.
For example, in one embodiment, a top level resource manager instance may delegate the provisioning of a Foundation as part of the operating session. In such a case, the top level resource manager instance and the lower level resource manager instance may negotiate the levels of service that the Foundation resources may provide to ensure the fulfillment of the purpose expression.
Lower level resource manager instances also have the option of performing their respective tasks in a recursive manner. In addition, a lower level resource manager instance has the option of notifying its superior resource manager instance that it cannot perform its delegated task for some reason. One reason may be that it itself does not have sufficient resources to perform the task. For example, the task may require that the lower level resource manager instance use a high-powered encryption service, to which it does not have access. Another reason may be that a resource specified by the task is not available and it cannot find an alternate resource. In such cases, its superior resource manager instance may need to find an alternate lower level resource manager or resource. If the superior resource manager is not the top level resource manager instance, then it also has the option of notifying its inability to perform the task.
In some PERCos embodiments, resources and resource elements may be arranged into classes and/or associate themselves with classes to organize them and to facilitate their discovery.
Resources and resource elements can be arranged into the following:
= Resource classes comprising resources, which are instances of resource classes = Component suite classes comprising components that contribute towards the implementation of resources;

= Method suite classes that specify the (externally visible) properties of the method embodiments;
= Resource interface classes that specify sufficient information to validly invoke methods of a resource instance.
This organization of resources and resource elements into classes enables PERCos embodiments to define interoperable, dynamic relationships between resource-related classes. For example, a method suite class instance of method suite class may have a relation, "is implemented by" with component suite classes, where the set of methods in the method suite is implemented by components in the component suite class instance of a component suite class.
Conversely, a component suite class instance of a component suite class may "implement" one or more method suite class instances. Resource interface class instances may include one or more component suite class instances and one or more method suite class instances.
Figure 7 shows an example resource instance that is an arrangement of a resource interface instance and resource element suite instance. This example resource interface instance, in turn is comprised of a PERCos identity Matrix (PIDMX which is described further in this disclosure) instance, kernel session instance and method suite instance. This example resource element suite instance is comprised of component resources and PERCos platform resources.
For example, as illustrated in figure 7, an example structure of a resource interface instance is shown.
Such organization of resources into classes enables utilization of many features of PERCos class system. Thus for example, a class system is a buffer against the scale of a boundless collection of resources and is a powerful tool in approximation computing. A class system may have hundreds of thousands or millions of classes. Class systems may substantially be used to represent conceptual neighborhoods for interfacing with user purposes (and/or users).
Frequently class systems may have permutations and/or be comprised of a constrained set of logical neighborhoods. Such constrained arrangements may be at least in part specified by acknowledged Domain experts, for example, functioning as Domain standardization/specification sets. Such class systems logically may be at least in part organized by, or otherwise include information associating resource classes and/or instances with, purpose expressions such as CPEs. Such purpose expression information may itself be correspondingly organized in class systems and both such class systems, as well as for example, crowd user data and/or Participant, Repute and/or Domain/category class systems may populate a common class arrangement populated at least in part by appropriate cross referencing. By starting a search for a resource that meets a purpose, with a search for the class that most likely contains the desired resource, PERCos enables the possibility of reducing a search space by several orders of magnitude.
Some embodiments of PERCos class systems may be relational, or may interface with other relational information organization structures (such as one or more relational class systems), to infuse such one or more embodiments with purpose related flexibility, which enhances user relational/conceptual navigation and evaluation processes. Thus for instance, the Open Directory Project (DMOZ, www.dmoz.org) is an ontology that implements certain relational organizational principles that can be similarly employed in PERCos purpose, resource, Participant, Repute and Domain class arrangements. A user of DMOZ interested in virtualization on Intel machines can traverse to a variety of computer virtualization solutions (VMware, VirtualBox, QEMU) in three simple and natural hops (Computer Emulators Intel x86 architecture). In a PERCos class system, the user could also use relationships other than the class hierarchy relationships to traverse the class system. This may be particularly useful in user cross Edge evaluations of purpose, resource, Participant, Repute and Domain approximation neighborhoods represented individually and/or in combination.
PERCos class systems may, in some embodiments, introduce their own standardized structured vocabulary for describing instances. To illustrate this, consider a user who wants to learn about VirtualBox virtualization where the host operating system is Linux and the guest operating system is Windows. Asking a keyword-based search engine to find this type of information can be time-consuming and frustrating, because a keyword of "Linux" is ambiguous in this search;
the "Linux" keyword can either represent the host or the guest operating system. As a result, the user may need to filter out retrieved results where the keyword matches because the Linux operating system is the guest operating system. This ambiguity would even occur if we assumed that the term "Linux" was totally unambiguous by itself; the ambiguity is not an issue with the different meanings of the "Linux" keyword but an issue with the relationship (e.g. guest vs.
host) between the VirtualBox and Linux. Thus ref/sense processing may not help in this situation. In addition, it may be that the user gets very different results by replacing Linux with nearby concepts such as Ubuntu (a Linux variant) or Redhat.
PERCos embodiments address this inadequacy by enabling the user to interactively unfold the user's purpose. The user forms a purpose expression of "learn VirtualBox." In addition, the user specifies a sophistication Facet of user variable Master Dimension to be moderate and a Repute Master Dimension of resources to be those whose authority is validated by Oracle Inc., the developer of the VirtualBox implementation.
The PERCos embodiment takes the user to the one or more neighborhoods of a "learn VirtualBox" waypoint and/or purpose class, or to any appropriate superclasses and/or super-waypoints, which are interim results that may enable the user to perform additional exploration.
In this case, an appropriate superclass might be a purpose class involving virtualization solutions in general which would include both VirtualBox and VMware. For either of these waypoints/classes, PERCos may provide additional information, such as, Acknowledged Domain Experts may have used the vocabulary of the PERCos class system to declare two Facet lists. One Facet list represents host operating systems (the operating system being used to run the virtualization solution) and the other Facet list represents guest operating systems (the operating system being emulated by the virtualization solution) operating system for the VirtualBox. The user can specify a guest operating system of "Windows" and a host operating system of "Linux" which may focus their experience on the VirtualBox platform that she is interested in learning about.
In some embodiments, class systems that include purpose classes may enable expressions of a wide variety of purposes and relationships. Such a purpose class system can include attributes that allow publishers to link resources which may populate one or more resource class arrangements, which may be comprised of inherited, declared, and/or inferred members, to purpose classes and/or members in one or more purpose class systems. By providing one or more well-defined standardized expression languages, PERCos embodiments can enable users and/or Stakeholders to formulate Purpose Statements that facilitate the maximization of the opportunity optimization.
PERCos, in some embodiments, provides unified, integrated, extensible purposeful computing Constructs. Resources may be combined in arbitrarily large and complex assemblages in pursuit of purpose satisfaction. In some embodiments, PERCos Construct templates provide a method of composing a set of resources, with their own descriptive specifications, resource interfaces, prerequisites, and/or other metadata into a single Construct resource, with its own descriptive specifications (CPE), resource interface, prerequisites, and/or other metadata. In some embodiments, Constructs comprising one or more component resources may be created by other processes.
Constructs embodiments can help enable users to efficiently and effectively create, build, arrange and/or instantiate specification arrangements that can be evolved, resolved, cohered, and/or transformed into operating Constructs in support of the pursuit of their purpose(s).
A Construct is, as applicable, a PERCos Formal or Informal resource arrangement.
Constructs may, in some embodiments, be created by Stakeholders including for example, publishers, and/or Acknowledged Domain Experts to provide users with optimal sets of resources and/or purpose-specific capabilities to aid them in their pursuit of purpose. Constructs may include, for example, Foundations, Frameworks, purpose class applications, and the like.
Constructs may also be created by publishers to provide highly specific resources for one or more purpose operations. This may, for example, include resource assemblies.
To support a wide range of purposes, from those that are highly general, such as "exploring mathematics," to those that are much more specific, such as "purchasing fishing lures for Bass in Lake Tahoe," Constructs are intended and designed to be highly expressive, standardized, interoperable, and extensible. Constructs can range from highly general to narrow and specialized. For example, a Stakeholder can create and publish a highly general Construct to explore western music, or a highly-specialized Construct to analyze Beethoven piano sonatas.
Stakeholders may also create and publish a single Construct that supports a range of purposes, from highly general to specific, by providing multiple Construct interfaces.
Construct interfaces can be used to specify purpose information, such as descriptive Contextual Purpose Expressions and/or Dimensions, to facilitate efficient matching of resources to users' prescriptive CPEs. In some embodiments, for example, users may use Dimensions to filter and/or reduce Result sets to those results (resources) with a high similarity to their expressed purpose.
For example, suppose a publisher created a purpose class application for "learning analog audio electronics" intended to provide an introduction to this purpose domain for users with limited experience. The Construct interface of this purpose class application may have Dimensions and Facets which enable a user to select values such as "Beginner" and "Simple". In such an example, the match of user purpose to publisher purpose may be close to ideal, subject to the user's experience with the purpose class application.
Constructs embodiments may provide, in whole or in part, purpose unfolding operations, for example in support of purpose formulation, e.g. supporting users in their expression of purpose, navigation and/or exploration and/or other associated interactions.
Some PERCos embodiments may use PERCos resource architecture to enable standardization and interoperability of computing elements that can be systematically combined and/or arranged into Constructs that support purpose operations.
Although any Construct may be used to support differing degrees of generality and complexity of purposes, some Constructs may be better suited than others Any and all of these Constructs may be used in combination as each constitutes a resource.
Constructs in some embodiments may also include, by reference and/or embedding, other specification sets that express purpose and/or other metadata (such as descriptive CPE) associated with the Construct.

Constructs may be of arbitrary complexity, and are associated with at least one specification that specifies at least one resource. Constructs may, for example, require further processing, such as, for example, by PERCos SRO processing, such that applicable and appropriate resources are suitably provisioned.
A PERCos operating agreement is a negotiated outcome. The PERCos operating agreement is expressed as a PERCos specification wherein resource managers and/or other operating session managers have agreed (implicitly and/or explicitly) to deployment of related levels of service and/or performance of specified resources, which are to be managed in accordance with the specifications comprising the operating agreement(s).
An operating agreement embodiment is a specification that has been implicitly and/or explicitly acknowledged and accepted by one or more resources. This may include sets of resources, including Constructs, where for example a single operating agreement is negotiated for and by the Constructs, Construct resource managers (and/or their delegate processes, for example PERCos SRO processes) may then implement appropriate operating agreements for those resources comprising such Constructs. An operating agreement comprises an identified set of resources, service performance, and/or resource management metrics within a common agreed specification.
In some embodiments, each resource identified by an operating agreement may be specified to operate at defined levels and conditionality of functionality. As an example, an operating agreement might specify high levels of service availability, reliability, security, and/or the like depending on Participant characteristics and/or, for example, the specific nature of the initiating user Purpose Statement(s). A PERCos Resource Management System embodiment may, for example, determine that the resource management needs to implement this requirement as a set of redundant services to ensure availability of at least one of the redundant services.
PRMS may interact with Coherence Services to negotiate, establish, harmonize and/or manage resources on users' and/or Stakeholders' behalf, and as a consequence, implement operating agreement provisions, which may include, for example, specifications for resource management, persistence, recovery from service delivery failures and/or arbitration between specifications.
In some embodiments, a PERCos purpose cycle comprises a collection of purpose-related processing that enables users to express their purpose, establish their contextual contexts, and manage the unfolding of their purpose experience. An example embodiment of purpose cycle, as illustrated in figure 8, may include the following processing:
= Computer Edge processing, = Participant Processing, = Purpose Formulation Processing, = Specification, Resolution, and Operational Processing comprising:
o SRO-S Processing o SRO-R Processing o SRO-0 Processing = Operating Session Processing For example, as illustrated in figure 8, an example of PERCos purpose cycle is shown.
In some embodiments, computer Edge processing may interact with users to evaluate and interpret their inputs, such as tokens representing ref/senses, to generate internal representations/structures, such as class expressions. Computer Edge processing embodiments may support users with one or more intelligent tools to assist them in expressing their purpose intent. For example, computer Edge processing embodiments may enable users to express their purpose intent by providing services, such as PERCos navigation interface that uses classes, Facets, PERCos templates, and/or the like to specify their Core Purpose comprising one or more verbs and one or more categories, and then refine it iteratively. Based on the user context, which may be established for example, by interacting with Participant processing embodiments, they may provide users with one or more appropriate standardized and interoperable lexicons, which are collection of tokens appropriate for some audience (e.g., English and/or Greek words, ASCII, Braille, or icons) and purpose domain (e.g., broadcast communication, box scores, parsing, science, organic chemistry, auto mechanics, plumbing).
In some embodiments computer Edge processing may enable users to modify and/or refine existing purpose expressions published by other Stakeholders such as, acknowledged Domain experts, and, for example, identified and sourced by PERCos intelligent tools, thereby optimizing user purpose expressions through leveraging the expertise of acknowledged Domain experts. For example, consider a user who may be interested in exploring financial investment.
Rather than expressing the purpose expression from scratch, the user could find a purpose expression that is nearest to the user's intent, such as, a purpose expression that explores different types of investments, ranging from fixed investment, a growth investment, and target-date retirement funds. The user may then narrow such a purpose expression by limiting indicated investment types to growth investment. This may be facilitated by an intelligent tool proffering of a faceting interface germane to the purpose expression whereby the user can select a sub-category.
User purpose session framing management enables users to interactively and iteratively establish their initial user context, which may be modified by subsequent processing, such as purpose formulation processing, SRO-S processing, and/or further PERCos processing.
Such management produces optimized purpose-related Foundation arrangements, involving at least a portion of resource capabilities, interface, information support, requirements, and/or the like for a given purpose expression set. Such initial user context may include information such as, a Participant Role a user wishes to use for such purpose operating session, applicable Master Dimensions, Master Dimension Facets, auxiliary Dimensions and/or further contextual information. Users may also provide authentication and authorization requirements, if appropriate. In some embodiments, such user purpose session framing management can operate in parallel with computer Edge processing, which may involve evaluating and then converting user inputs into internal representations.
Purpose formulation processing, in some embodiments, can iteratively interact with users to generate one or more purpose specifications that may be the "best attempt"
(after interacting with PERCos) by users to frame their respective purposes. They may generate purpose specifications by incorporating applicable contextual information, such as, without limitation, Master Dimensions and Master Dimension Facets, resonance, governance, and/or crowd data.
For example, some users may have their user characteristics and historical data stored in an information management system, such as, a PERCos Platform Information Management Systems implementation. Purpose formulation processing embodiments may retrieve and evaluate such contextual information and incorporate information that is applicable in generating a purpose specification, such as a Purpose Statement. They may also support improving purpose specifications by using applicable resonance algorithms, if available. If they encounter possible problems, such as, ambiguities, conflicts, and the like, they may interact with Coherence service instances to resolve them. If they cannot, then they may request guidance from appropriate processes and/or users. Users may also provide additional contextual information, such as, for example, augmented Dimension values, such as, a preference for comprehensiveness of Outcome over speed/promptness of response time.
In some embodiments, Specification, Resolution and Operational (SRO) processing comprises one or more integrated sets of processing that evaluate, resolve, transform, and/or cohere purpose specifications to generate one or more resolved, cohered, and provisioned operating specifications that have sufficient information to initiate the launching of one or more operating sessions. SRO processing utilizes PERCos Platform Services, such as, for example, Coherence Services, Evaluation and Arbitration Services, Test and Result Services, Repute services, and/or the like to provide its services. SRO processing may also use intelligent tools, such as PERCos Information Management System tools that they may use to leverage knowledge captured from past experiences. It generally performs its services in three phases:
specification, resolution and operational.
SRO-S processing embodiments evaluate purpose specifications and may incorporate relevant contextual information, such as, user Master Dimensions and Facets, user historical information, resonance algorithms, Foundations, governance, crowd data, and/or other information, such as, additional user purpose relevant profile information. SRO-S processing resolves and integrates these specifications, often in collaboration with one or more other PERCos platform processes including Coherence to generate a Purpose Statement that is sufficiently complete.. The above Purpose Statement may include various types of the user's contextual information (e.g., her level of expertise in a particular purpose Domain, education level, location, time, and/or the like).
SRO-S processing embodiments may evaluate applicable governance rules to ensure that they are compatible with a user's purpose and context. For example, suppose a user is an employee of an organization that may have governance rules on resources the user may access, such as prohibiting the use of "insecure" resources that may tamper with the organization's resources.
SRO-S processing embodiments may also evaluate a user's Foundation resources to check that the resources can support the user purpose. For example, SRO-S processing embodiments may check that the platform a user is using is compatible with any digital rights management requirements specified by the relevant resources to fulfill user purpose.
SRO-R processing embodiments may take a Purpose Statement -- generally generated by SRO-S
processing -- and generate an operational specification that specifies one or more resource sets that can fulfill the Purpose Statement. SRO-R processing interacts with one or more resource management systems, such as, PERCos Platform Resource Management Systems (PRMS) to assign, allocate, and/or reserve resources that are suitable for fulfilling such Purpose Statement.
In some cases, SRO-R processing may request clarification and/or elaboration from users/Stakeholders, for example, in an iterative and or recursive manner. For example, consider the case where a user is not authorized to access some resource. In such a case, if SRO-R
processing cannot find an alternative or substitute resource, it may request guidance from users and/or Stakeholders to resolve the conflict. This may, in some cases, require modification and/or re-specification of the Purpose Statement, or, for example, a user CPE.
Another example may be where the user has insufficient expertise to evaluate the resource opportunities and SRO-R processing may invoke one or more other processes, such as, one or more resonance algorithms that may offer one or more Constructs providing optimized resource arrangements that may better satisfy a user's sets Purpose Statements.

In some embodiments, SRO-0 processing undertakes the provisioning, deploying and/or instantiating of resources specified by the operational specifications and subsequently initiates launching of one or more operating sessions (including initiating resources into operating resources and/or invoking one or more processes and/or services) as specified.

processing may, in some cases, create multiple other user purpose operating sessions and provision them with the launched operating resources.
User purpose operating sessions interact with users to provide them with one or more interim and/or final Outcomes that in part or in whole meet their respective purpose specifications.
Operating sessions may also include the negotiation of one or more operating agreements with PRMS operating managers that can specify levels of performance of one or more resources, processes and/or services in pursuit of purpose expression.
Such operating sessions may enable users to manage their sessions, such as suspend, resume, replay, persist, and the like. For example, users may opt to persist one or more operating sessions in order to publish them as resources. Alternatively, for example, users may persist/suspend their operating sessions in order to be able to restore/resume it at a later time.
Users might terminate one or more operating sessions because they may be satisfied and/or reached a conclusion, and/or the user has for other reasons decided to terminate the session.
In some embodiments, purpose cycle processing may be iterative, recursive, serial, parallel, asynchronous, synchronous, preemptive, multitasking, multi-threaded, and/or employ other multi-dimensional methods for resolving users' purpose expressions to Outcomes. For example, one or more specifications (including purpose expressions, purpose specifications, and Purpose Statements) may be modified either by users and/or by one or more PERCos processes.
For example, PERCos SRO-S processing may encounter a conflict when generating a Purpose Statement. At this point, SRO-S processing may invoke Coherence processing to resolve the conflict, however where it cannot, it may provide information regarding the conflict and/or potential solution/opportunities to the processing (including the management thereof) from which the specification originated, for example in this case purpose formulation process.

Purpose formulation processing may represent this information, including the affected Purpose Statement in a manner suitable for user interaction. This may include the conflict, opportunities for the conflict resolution, guidance as to potential optimizations and/or rationalizations for the users expressed purpose.
For example, SRO-S processing may not be able to resolve possible ambiguities in Purpose Statements. For example, suppose a user specifies a purpose to learn about Java. There may be multiple ref/senses that contain the term "Java", such as coffee Ref/Sense, programming ref/sense, island ref/sense. SRO-S processing may attempt to resolve this ambiguity by evaluating the purpose expression. SRO-S processing may request for elaboration of the user's intent, such as Java as in a type of coffee, programming language, or an island.
A PERCos operating session may comprise a set of managed functioning operating resource sets that can provide PERCos-related purposeful cross-Edge user interaction. As illustrated (Figure 9, Figure 10) an operating session is initiated from a set of specifications, such as, control, organizational and interface specifications, that define the functionality of such operating session, and unfolds until users/Stakeholders interventions and/or satisfaction, termination, and/or other completion of the session's PERCos processes. Participating processes may take place in one or more users purpose operating sessions (including for example cross-Edge processes), in and/or among users' accessible computing arrangements, and/or in other available computing arrangements (e.g., computational clouds). The set of specifications may specify the composition and/or organization of operating session interface, which can be anything from a minimal set of interface elements to a full complement. Depending on the embodiment and/or the operational environment, the operating session interfaces may operate distributed, peered, hierarchical arrangements and/or in any combination thereof. For example, in Figure 9, a single operating session interface provides the interface, whereas in Figure 10, the interface is provided by multiple operating session interfaces, two of which operate in a peer-to-peer relationship and the other two in superior-subordinate relationship.
For example, as illustrated in figure 9, an Operating Session Embodiment (single session interface) is shown.

For example, as illustrated in figure 10, an Operating Session Embodiment (multiple session interface) is shown.
An operating session that is provided with an operating specification, comprising control, organizational and interface specifications, may assist users in their ability to pursue their respective purposes. There may be other operating sessions that interact with users to formulate purpose specifications which can be transformed into operating specifications that can be used to provision, deploy and/or instantiate resources for the subsequent instantiation and/or launching of one or more operating sessions.
Some PERCos embodiments may associate contextual information of one or more users with operating sessions in support of fulfillment, which may include for example, one or more resonance algorithms to support in part optimization of purpose. This context may evolve as the operating session progresses and unfold. In some situations, a user and/or PERCos computing environment may start one or more sub-operating sessions with suitably modified contexts.
In some cases, an operating session may create a new operating session to accommodate one or more context changes. For example, consider an operating session shared by multiple Participants. Some of the Participants may have different or even contradictory context elements. In such a case, a PERCos embodiment may create multiple operating sessions, one or more sessions for each context. And yet, these operating sessions interact with each other to fulfill the shared purpose.
In some embodiments, operating sessions may be forked, persisted, restored, suspended, resumed, and/or terminated. Users may fork an operating session to try out different methods to achieve a purpose. Users may persist an operating session in order to publish it as a resource.
Alternatively users may persist/suspend an operating session in order to be able to restore/resume it at a later time. Users might terminate an operating session because they may be satisfied and/or reached a conclusion, and/or the users have for other reasons decided to terminate the session.

In some embodiments, one or more operating sessions can have operating specifications which include one or more operating agreements. Operating agreements are negotiated between operating session managers and resource managers, such as PERCos Platform Resource Management System instances. In some embodiments, operating specifications may be persisted when an operating session is persisted so that they can then be restored when the operating session is restored.
A PERCos embodiment may address the unique requirements and challenges of purpose-based computing and one-to-boundless resource management by providing some or all of the following capabilities:
= Store, administrate, manage, and/or provision resources in a manner corresponding to purpose expression and enable optimal purpose satisfaction.
= Employ reusable/re-purposeful resource sets to support purpose-responsive user experience.
= Provide interface capabilities to Big Resource, that is an extremely large and varied resource set, including all resource types and arrangements, and including optimizing distributed topological resource arrangements and stores that are responsive to unique, dynamic purpose requests through the use, in part, of lossy class ontologies and matching and similarity analysis.
= Provide a scalable, interoperable, extendable, and distributed architecture for describing and/or organizing resources and/or information about resources for unbounded sets and types of both PERCos-enabled and non-PERCos resources (e.g., legacy and external services).
= Enable uniform treatment of the spectrum of resource types, their operations, and/or associated information.
= Provide methods and system infrastructure to manage PERCos and non-PERCos resources optimally.
= Provide interoperable/standardized resource interfaces and interface components for PERCos resources.

= Provide systems and methods for creation, including efficient dynamic creation, of resource arrangements and associated resource management mechanisms, including managing any such resource arrangements as a single resource, and optionally in combination with any other one or more resource arrangements.
= Provide systems and methods of harmonizing PERCos resource arrangements using service types and combinations used, for example, by PERCos Coherence sub-systems.
= Provide monitoring and exception handling so as to store information regarding, and support identifying and/or testing of resources to avoid failure, optimize efficient operation, as well as respond to failure, so as to enable in whole or in part predictive, efficiency optimizing, corrective, recovery and/or regenerative processes.
= Provide a spectrum of resource governance services including authentication and authorization (A&A) management and stakeholder rule enforcement and interest optimization.
= Provide fungible identity services for identification, association, management and/or maintenance of identity information regarding PERCos and/or non-PERCos resources in aggregate, contextually constrained (e.g., in association with purpose), and handle unique identifier forms.
= Provide systems and methods to persistently and operationally efficiently store resources and/or information about resources in local, cloud, and distributed topologies, including for dynamic generation.
= Provide publishing services for resources, including managing/administrating underlying contributing resources and flexibly representing stakeholder interests and prescriptive and descriptive purposeful operations.
= Provide distribution services for resources and/or information about resources.
= Provide resource discovery, assimilation, analysis, and/or matching/similarity services, including integration with platform and network Coherence processes.
= Provide resource scheduling, reservation and allocation services.
= Manage PERCos and non-PERCos resources optimally.

2 Resource architecture This section considers potential implementations of PERCos specifications, PERCos resources, PERCos Platform Services, PERCos Information Management (PIMS), PERCos Identity Systems (PERID) and PERCos Hardware and Devices In some embodiments, a PERCos system is a network operating environment for purposeful computing, extending traditional operating system capabilities by, for example, uniquely enabling user expression of purpose, and further employing apparatus and methods for optimally matching user Contextual Purpose Expressions (CPEs)¨and any applicable associated preferences and Foundation, user, and other Stakeholder rules, metadata, and/or the like information ¨to resources available locally and/or on one or more networks. A
PERCos system is designed to support the deployment of resources to provide user purposeful results that are responsive, at least in part, to user purpose expressions.
With PERCos, users can intelligently and efficiently interact with a global, nearly boundless "purposeful network," comprising an immense diversity of possible resources that are aggregatable and configurable as purpose-responsive arrangements. A feature of some PERCos system embodiments is their inclusion, organization, and management of all potentially actively contributing elements of a session as components of a logically unified resource infrastructure.
Processing elements, any and all contributing forms of information, any and all contributing forms of network resources, device arrangements, and Participants, can be uniformly treated as resources. They may be aggregated, and are identifiable, assessable, and deployable in response to user purposes. Computer memory, devices, microprocessors, databases, software, services, networks, Participants, and other specification types may all be managed by PERCos resource managers.
PERCos resources can include information resources, computational resources, communication resources, computer representations of users, and/or other resource types.
Common kinds of resources include content, hardware, devices, software, services, Participants, and/or networks.
PERCos can flexibly support the organization, provisioning, and purpose-related governance of a potentially boundless collection of possible resources, normally with the goal of achieving optimal responses or response candidates to purpose specifications.
A PERCos embodiment may include a distributed and hierarchical resource architecture that provides a uniform treatment for resources regardless of their size, complexity, diversity, location, format and/or methods of their creation.
Resources, in general, are operatively associated with at least one resource interface arrangement. Common kinds of values that can be named include data/contents, and/or specifications for such data/contents, hardware, devices, processes, software/applications, and/or networks. Resources may be PERCos interpretable.
In some embodiments, PERCos resource architecture provides two methods:
assemble and disassemble, where:
= Assemble method takes a collection of resources, R1, Rk, and creates a new composite resource, R, with an associated resource interface that enables other resources to access Rs through R's resource interface.
= Disassemble method takes a resource, R, whose organizational specifications may specify whether R can be decomposed, and if so, how.
In some embodiments, a resource interface provides sufficient information to validly invoke operatively associated methods of a resource instance.
In some embodiments, PERCos resources include interface specifications, organization specifications and control specifications, which may refer to resource elements comprising resource and/or resource interactions with other resources.
Figure 11 is an example of an embodiment of a resource item. It shows that a resource is instanced by sending a message comprising control, organizational, and interface specification where interface specification may be for both Application Programming Interface (API) and user interface. Once a resource is instanced, it can accept inputs and generates outputs.

Platform resource Management Services utilizes this consistent method of creation to uniformly organize and process resources, including providing common service/resource management interfaces for individual and/or groups of resources in a seamless manner.
In some embodiments, PERCos resources have one or more unique identities (UIDs) that can be used to access the resource, including its resource interface.
In some embodiments, PERCos resources are composed of one or more resource elements.
PERCos resource architecture supports a wide variety of ways of declaring resource elements and/or organizing them, such as, for example, a hierarchical organization, into compositions of resource elements. Resources may also be embodied in various ways, including ways in which their representation is at least partly implicit.
For example, the resource embodiment shown in figure 11 comprises the following resource elements:
1. Resource interface including method specifications, kernel session, resource specifications suite (including control, interface and organization specifications) and resource PIDMX.
2. Resource body including of method implementations and resource components (elements).
In some embodiments, PIDMX that is used by resource interface (e.g., operating session Coherence Manager) to reason about the resource's relationship with other resources is grouped as part of component resource element. Whenever the resource interface needs to access its PIDMX, it may interact with its component suite. Other embodiments may have somewhat different resource elements and/or different ways of organizing them into composite resource elements. For example, there may be an embodiment in which PIDMX is its own separate resource element.
This flexible way of defining resource elements and organizing them enables a resource architecture embodiment to provide multiple resources that have the same functional capabilities but, for example, differing performance and/or location, to support differing operational environments. For example, a resource architecture embodiment may provide two resources, one for a limited platform operating environment and another for a super computing environment with powerful servers. For the limited platform environment, it may provide a version of the resource that may be configured with a minimal set of resource elements, such as an extremely light-weight resource interface comprising a kernel session and a set of UIDs of method specifications. In particular, the resource's method specifications may reside elsewhere, and the resource would access them on demand basis, using their UIDs.
PERCos resource architecture may include resources that have single or multiple resource elements in any arrangement. However, regardless of how they are organized within and/or by the resource, whether they comprise for example, only those interface elements or comprise a resource set (which may for example include other resources, for example those on which the resource described has a dependency), are distributed, embedded, referenced or arranged in whole or in part in other manners, such resources are accessed, through one or more PERCos resource interfaces in a standardized and uniform manner.
For example, as illustrated in figure 12, a resource embodiment is shown.
The design aspects of this embodiment of PERCos resource architecture include:
= Platform independence = Scalability = Reliability and resilience PERCos resource architecture embodiments may achieve platform independence by treating all their relevant computational elements uniformly as resources. Thus different conventional operating platforms such as PERCos, Windows, OS/X, Linux, FreeBSD, and others are considered simply as Foundations (e.g., as a type of resource). As resources these Foundations may have resource interfaces and interface specifications. For example, resource architecture embodiments may not need to give any special treatment to a Foundation that represents a Linux operating system as opposed to a Windows operating system; if the specification of the Linux Foundation meets the requirements of a particular Construct, for example "Framework, template" then it can be utilized by that Construct template.
Other platform specific features may be treated in a similarly uniform fashion by a platform independent PERCos embodiment. An authentication scheme based on a Lightweight Directory Access protocol (LDAP) implementation and an authentication scheme based on the Microsoft Active Directory implementation may be simply represented as resources by a PERCos resource architecture. If these resources implement a common interface, then they could be used interchangeably by various resource arrangements.
A PERCos implementation may further support platform independence by utilizing technologies that have support across different platform architectures. Thus a PERCos embodiment that users access primarily through a web browser could make heavy use of the HTML 5 and JavaScript technologies. Any Construct that includes resources that provide HTML 5 and JavaScript functionality would then be compatible with any user Foundation which included a web browser.
To support one-to-boundless computing, PERCos embodiments may dynamically arrange arbitrarily large number of resources in support of purpose sets. For example, consider a virtual lecture that may be attended by millions of students. The organizers of such a lecture may desire to manage the students, in order to check their prerequisites, collect fees, provide certification, or the like. The management data structure should be scalable to deal with such large number of students. In addition, at this scale, the management data structure should be highly reliable; losing access to the billing system may cost the organizers money and create inconvenience for students who need certification.
PERCos resource architecture embodiments may address scalability by providing the following capabilities:
= Dynamically create, arrange, and manage resource arrangements that comprise vast number of resource elements, = Dynamically allocate relevant resources, as appropriate, = Provide control specifications that express operating requirements, such as replication, fail-over functionality, desired level of band-widths, = Provide organizational specifications that express the organization of resources, such as peer-to-peer, hierarchical, hybrid, and the like, = Provide interface specifications that provide a set of methods, and/or = Provide operating agreements that specify agreements between the consumers and providers of resources.
Resource architecture embodiments may support scalability and adaptation by enabling a group of resources to be arranged and/or otherwise transformed (e.g., algorithmically related and/or ad hoc arrangements) into a single functionally more capable resource, which, in turn, can be arranged and/or otherwise transformed with other resources to create even more capable resources. This enables creation and use of resources at any chosen level of granularity so that users may experience, organize, store, and/or publish computer sessions and session elements that provide the best fit to their purpose.
Supporting one-to-boundless computing may involve a PERCos resource architecture to enable PERCos systems embodiments to interact with non-PERCos-external systems whose resources may not support basic PERCos resource properties in a manner that enables direct interaction with PERCos resources systems embodiments (for example including PERCos resources and/or PERCos Platform Resource Management Services). Such resources, when used in conjunction with a PERCos system, are called non-PERCos resources (NPR). Typical examples are legacy hardware, legacy databases, legacy software, and non-PERCos services.
One aspect of this approach is that the complexity of connecting a new kind of resource to a PERCos system depends only on the complexity of the resource's native interface and the amount of "fitting" work that may be required in the transformer to implement a suitable resource interface. It does not depend at all on the size of the PERCos system, the number of kinds of PERCos resources, or the number of other kinds of non-PERCos resources that are interfaced to the system. This independence is a practical result of one-to-boundless operation.

In some embodiments, a transformer is an element that, when combined with a non-PERCos resource, provides the properties of a PERCos resource. A transformer may comprise sufficient information to identify a unique element (value) and associated resource metadata, including one or more associated resource interfaces¨from within the transformer and/or from some other source.
A non-PERCos resource may be associated with more than one transformer; each transformer-resource combination represents a distinct PERCos resource.
In some embodiments, non-PERCos resources can be converted, using suitable transformers, into resources suitable for interaction and integration with PERCos resources and management systems (for example PERCos Platform Resource Management Services) and are described as informal PERCos resources.
An assimilator is an element that identifies a non-PERCos resource through name, location, and/or reference identification and enables PERCos to access it by invoking appropriate one or more transformers.
For example, as illustrated in figure 13, an assimilation of non-PERCos resource into PERCos environment is shown.
A PERCos embodiment may enable comprehensive reliability by provisioning a set of health checking platform services that act to support operations, from user inputs and formulations through to operating resources and user experience. In some embodiments, each resource and associated processes may undergo processing provided by PERCos Platform Services, such as Evaluation, Testing and/or Monitoring Services supported by Identity, History, Persistence and/or other Platform Services. In some embodiments, PERCos Coherence Services may provide a combination of these capabilities in response to specifications that express reliability and/or comprise reliability metrics.
In some embodiments, resources may provide specifications detailing their reliability, expressed in the form of metrics, and in some embodiments, for example, these may be expressed in the form of Repute expressions. Such assertions may be supported, in whole or in part, by testing and verification services, which may provide assertions on such Repute expressions, for example a Repute Cred on a Cred.
Reliability may incorporate such techniques as redundancy, such as providing hot standbys that can replace failing resources. For example, the Byzantine algorithm is another way to provide reliability. In some embodiments, resources may be periodically monitored and/or persisted, by for example PERCos Platform Monitoring and/or Persistence Services, such that if a resource faults, it can restore resource(s) to its previously persisted state. For example techniques such as those used in transaction processing systems, for example rollback, failover, fault tolerance and the like, may also be used, as may other common techniques such as check pointing.
If a resource's component resource fails to comply with its functional specification, PERCos Platform Resource Management Services can, in some embodiments, replace the failing component resource. A resource architecture can also provide a uniform mechanism for substituting for missing components, responding to a wide variety of component failures, dynamically adding or removing components, incorporating legacy components, and/or optimizing component selection.
Operating agreements may incorporate appropriate service, performance, reliability and/or other specifications, and may further include specifications that instruct other PERCos Platform Services, including: Evaluation Services, Arbitration Services, Monitoring and Exception Services with appropriate further specifications (including for example, instructions, metrics, resources) as to response and initiation methods. PERCos embodiments may utilize a variety of techniques and methods to achieve the requested reliability specified by the operating agreement.
PRMS may use an embodiment of PERCos Test and Results Services to perform diagnostic tests on a periodic basis. Before a resource is provisioned, a PRMS can perform the tests associated with the resource and then check that the test results match the resource's specification. In addition, even while the resource is operating, a Platform Resource Management Service can perform the tests. For example, it can sample communication channels to measure their loss rates, bandwidths to ensure that the channels satisfy the needs of the contextual purpose experience session.
PERCos embodiments, through the provision of standardized PERCos resource interfaces enables users through their expression of purpose, methods for effective interaction with Big Resource In some PERCos embodiments these standardized resources interfaces for each resource roles-standardized interactions provide a standardized "plug and play" capability that can be accessed by users in their unfolding purpose operations.
In some embodiments, resources may have one or more standardized and interoperable Roles associated with it, which are expressed as one or more specifications based on one or more classification systems, which in some PERCos embodiments may include standardized and interoperable specifications. These specifications may be human interpretable.
These Roles may, in some embodiments, form a class. For example a Participant may be associated with Role administrator, for one or more purpose operations and/or a resource Role may be a standardized PERCos embodiments Information resource.
Resources (and/or arrangement thereof) may be classified by one or more classification schemas, including for example PERCos standardized schemas. Roles may be associated with one or more resources comprising functional standardized and interoperable operational arrangements, such as for example, information store, processor, and the like.
In some PERCos embodiments there may be one or more resource classification schemas which may also be mapped to each other and/or from classes.
Example Roles of resources may include, but are not limited to:
Information, ¨ Processing, ¨ Query (Search), ¨ Storage, ¨ Methods, ¨ Communications, ¨ Interfaces (Display/Audio/Sensor), ¨ Participants, ¨ Resource managers, ¨ and the like.
In some embodiments, certain aspects of Roles may be quantized and have interoperable and/or standardized expressions and/or representations. For example novice, expert and the like may have PERCos embodiment wide definitions. These, for example in some embodiments, are user variables Master Dimensions Facets, and as such may serve as both the name of a Role as well as a Dimension.
Users and/or other Stakeholders may have representations across the Edge in a PERCos embodiment computational domain, called Participants, which are PERCos embodiments resources. These may have associated Roles, such as "Tech Support Guru", "authorized Signer", "VP Sales", "Lawyer". In some embodiments, Participants may also have multiple associated Roles.
Roles may have one or more profiles associated with them, including preferences, which may be applied/included in purpose operations involving Roles. Roles may be purpose class specific.
For example within a specific organization, there may be one or more hierarchies of Roles with associated rules and/or other specifications (for example rights/entitlements/tokens/capabilities and the like).
Each resource Role may have one or more sets of specifications describing resource characteristics and/or functionality for one or more purposes (which may include associated metrics). For example an information resource may indicate its associated PERCos embodiment and/or embodiments categories.

In some PERCos embodiments, resources may have standardized resources interfaces for each resource roles-standardized interactions, in this manner providing a standardized "plug and play" capability that can be accessed by users in their unfolding purpose operations. Resources of differing complexity, functionality and/or other characteristics may be interchanged when their Roles are by specification sufficiently the same. Standardized resource Role interfaces support this interoperability. In this manner users may, for example, select differing resources for a given purpose fulfillment scenario, such as, for example, satisfying purpose fullment using more or less complex, sophisticated, and/or detailed information resources, processing resources, management resources and/or the like.
For example in some embodiments, there may be one or more classification schemas associated with resource Roles, for example an information resource classification may comprise text book, video/audio, reference text and the like.
Such resource Role specifications may be independent of the resources that they specify, such that one or more PERCos embodiments specification frameworks, for example PERCos embodiments Constructs such as for example Frameworks, Foundations and the like, may comprise sets of specifications that are arranged by resource Roles.
In some embodiments, resource Roles may include resource types which are subtypes of a higher order resource set that characterize resources with useful collections of attributes in common. These types may be standardized and interoperable and may be constrained by one or more purposes, for example constrained by Core Purpose. For example a Role may be "Teacher College Physics". In some embodiments, Roles may comprise sets of resources associated with one or more purpose operations, for example the Role "Tube Audio Power Supply"
expert may require that certain specific resources have been regularly accessed by that user.
Many resources may have one or more methods in their method suites, which may be used to further classify resource Roles, such as by their sets of methods, descriptive purposes, semantic ontologies (e.g. associated CPEs, metadata and/or subsets thereof), functionality, locations (local, group, external), scopes (private, limited, public), and/or accessibility (assumed, required, available, or potentially discoverable).
For example, input device, output device, communications channel, relational database, word processor, accounting service, and Participant may be, in some embodiments, resource Role types, and many of them may have an extensive structure of subclasses (e.g., Keyboard, PS2 Keyboard, USB Keyboard, Ergonomic Keyboard; Display, PixelMap Display, Raster Display, Low-def Display, Medium-def Display, High-def Display), allowing description of any relevant attributes to any selected degree of precision.
Roles may be considered, in some PERCos embodiments, as a further type of identity (in addition to the identity of the resource), which may be in the form of a resource associated with one or more Participant representations. In some embodiments, PERCos embodiments Participant may have their associated Roles (which may be declared and/or attributed) registered, by one or more utility services.
Roles may be formulated as schemas, which may, in some examples, be presented as classes.
In some embodiment, Roles may have associated specifications, which may include principles such as, "least privilege", rules, rights (such as administrator), and the like.
In some embodiments, structured Roles may include those whereby there is a defined relationship between and/or within Roles, for example a hierarchy of Roles which includes:
= Stakeholder Roles whereby Stakeholders define hierarchy of Roles and/or relationships of Roles, including specifications that determine Roles interactions, for example employee, officer, manager and the like.
= User Roles may be structured such that user determines, through for example specifications persisted as preferences, the rules by which Role may interact with other resources and/or operations.
= Affinity group Roles, where for example formal Role within the group, (for example affinity group secretary) and/or informal de facto role, (for example leader of subset of affinity group faction) roles within affinity groups. These in turn may be internally structured (as with user Roles) and/or externally structured (as with Stakeholder Roles) and/or any combination thereof.
In some embodiments, Roles may comprise pre-determined arrangements of context (preferences, purpose profiles, resources including specifications such as for example rules) which may be used in purpose operations where, for example, structured Role (for example customer of type (N) for company (Y), Frequent Flyer of airline (N) and the like) interacts with user purpose operations, including for example purpose class applications, where the interaction includes at least one pre-determined purpose.
In some embodiments, there may be PERCos embodiments defined Roles that are part of those PERCos embodiments, including for example publisher, user, administrator, sovereign bodies, and the like.
For example PERCos may support specifying that a given Participant have the role of publisher Stakeholder in a given context. Such a Participant may have to undergo one or more interactions with PERCos compliant resources, such as a utility, to, for example, establish and validate her identity and such associated Role.
Contextual Roles may include one or more contextual aspects such as location, temporal, complexity, expertise and/or any Dimensions and Facets, and/or the like.
Contextual Roles may use session specific dynamic specifications to establish the relationship between resources and/or users/Stakeholders. In some embodiments, contextual Roles may not effectively carry persistent authority across multiple sessions and/or be represented by such information organizations as class systems.
In some embodiments, contextual Roles are "of the moment" representing that set of contextual aspects that determine the Role of Participant within unfolding experience and associated processes.

Contextual Roles may be dynamic, in that the context of the user interactions may vary as they discover resources during their purpose operations.
Within many social structures and relationships there may be social Roles which determine the relationships between the users with those Roles. For example these may be declared such as familial (for example Son, Daughter, Father), Follower/Leader (for example one user 1 declares he follows user 2 or user 2 leads group of users X), Influencer/Influenced (for example x influences y or a is influenced by b- all of which may have metrics of such relationship expressed/implied/calculated) and/or comprise associative relationships, such as for example friend, colleague, associate, acquaintance and the like.
The degree to which these social roles and/or Role related Participants may be stated and/or inferred may be further influenced by the associated Reputes of those Roles, which may incorporate in whole or in part the Reputes of one or more Participant and/or other resource associated with the Roles.
In some PERCos embodiments, support for one-to-boundless computing through managing all types of resources¨regardless of their type, internal interfaces, and/or their method of creation¨may be achieved through using a unified resource interface framework.
Resource interfaces can act as proxies for all interaction with other resources. An instance of a resource interface is defined by a resource interface specification, which in addition to specifying methods, which in some embodiments may be a method suite, may include control, organization and interface specifications, comprising a resource specification set.
A resource interface representation may comprise anything from a minimal set of resource interface elements to a full complement. Depending on the embodiment and/or the operational environment, a resource interface instance may be distributed and/or some of its components may be offloaded to its resource's component suite.
In some embodiments, a resource interface on a platform that has limited resources (e.g., a smart phone with limited memory), may comprise a minimal small set of resource interface components. Moreover, the resource interface may store only those components that are essential for bootstrapping its operations on the platform, and offload the rest to the resource's component suite to be accessed only as appropriate. For example, if a resource interface had offloaded its metadata and its kernel session, then relevant metadata information (e.g., performance characteristics of a component resource might be obtained from its component suite "on demand."
By contrast, if a resource interface is on an operating platform with ample computing power and memory, then it may comprise a full complement of components on its platform, including its metadata.
In some embodiments, a resource interface may be distributed across computing platforms or networks. For example, its method suite may be distributed so that some of its method specifications and/or implementations are stored in one platform, and the rest are stored on others. In such a case, the resource interface on one platform may serve as a proxy for components on other platforms.
In some embodiments, an invoker of a resource set may not be fully aware of the resource set's implementation details, for example, such an invoker may be aware of some or all of the resource set's higher level capabilities, but may not be aware of certain or all of lower level functions, such as, for example, some or all component calls and/or the like.
For example, an invoker of a resource set, say R, may not know that R is operating on a platform that may require R to offload some of its resource interface components or to operate in a distributed manner; it is accessed in exactly the same way as when R is operating on a platform with ample resources and can provide all its services using only local resources.
A PERCos embodiment may provide a variety of ways to construct a new operating resource depending on operational environment or implementations. For example, one embodiment can be analogous to the way UNIX shells spawn child shells. In UNIX, any collection of shell commands may be stored in a file, called a shell script file. A shell allows creations of a new user interface for UNIX operating system by spawning a child shell and specifying a script file.
In PERCos, a resource may construct a new operating resource instance by specifying a resource specification. The construction may be performed in multiple ways. For example, initially a new resource interface may be created by instantiating a resource type using one or more resource specifications. Such instantiation may create a resource whose resource interface contains a method suite instance comprising a set of methods specified by the control specifications (see Figure 14). Subsequently a kernel session instance may be activated as part of the resource interface (see Figure 15). At this point, the resource interface is operational and can choose to determine the location of the rest of its components, such as its communication interface suite, PIDMX, and metadata.
For example, as illustrated in figure 14, Part 1 of operating resource creation example 1 is shown.
For example, as illustrated in figure 15, Part 2 of operating resource creation example 1 is shown.
In some embodiments, another way of creating an operating resource is to create a resource interface including of a kernel session instance. The kernel session instance then interacts with its control specification(s) to create operating resource (step 1 of figure 16). The kernel session instance can store its control specifications as part of its resource interface. It may also cache its resource interface specifications so that it can optimize the resource creation (step 2 of figure 16) For example, once kernel session instance obtains the resource interface specification, it can complete the contruction of the rest of its resource interface components, such as, for example, obtaining appropraite method suite(s). It also creates the resource body comprising the method implementation suite and component suite. Caching the resource interface specification may optimize this process (see figure 17).
For example, as illustrated in figure 16, steps 1 & 2 of operating resource creation example 2 is shown.
For example, as illustrated in figure 17, step 3 of operating resource creation example 2 is shown.

In some embodiments, resource interface acts as proxy for all interaction with resource components. In some embodiments, it handles all rule-based interactions, for example authentication, authorization, credentials, certificates and/or other security and/or governance specified by resource components and/or specifications for use of resource and may involve resource interface maintaining such rules (for example certificates) for the resource component(s). Another example may involve the resource interface interacting with a PERCos rules manager instance to handle one or more rule sets on behalf of the resource, including those utilized by the resource interface itself to bind to the resource components.
PERCos resources interfaces may be individually instanced and/or support a plurality of instances for resources and/or resource arrangements. PERCos resources may be implemented as, for example a single service executable and/or as a group of service executables that act as one.
The resource interface may have one or more rules sets (including for example governance, authentication and authorization, or other rules and/or policies associated with it that constrain the origin, types and numbers of messages that may be sent to it), and further may have additional rules and/or policies regarding the handling of those communications (including for example messages). For example a resource interface may only respond to messages from specific Participants (and/or other resources), and/or identified processes and/or communications/message types. In some embodiments this could be defined by, for example, an organization that may restrict access to one or more of its resource to only authorized employees only ¨ i.e., those Participants that present appropriate identity credentials.
The resource interface may also manage low level call failures (for example including implementing low level authentication and/or authorization failure recovery) on behalf of the resource Fabric instances. Persistent call failures may be notified to the requesting RSM and/or other calling resources and/or processes to which notification communications/messages are specified.

In some embodiments, this may involve testing that includes reality integrity analysis, whereby for example the veracity of a video image is validated as being the real time image of the user, supporting his assertion to be whom he asserts to be.
Resource interfaces may interact with other PERCos Platform Services, as that may be required to satisfy specifications, for example where such specifications may require invocation of platform services to achieve a specific Outcome. For example, the resource interface may interact with PERCos Persistence Services instance to persist that set of information that the resource interface is responsible for, such as, metadata and/or operational performance information. In some embodiments this may also include interaction with PERCos Coherence Services so as to reconfigure that resource interface's component resource arrangements.
In some PERCos embodiments, resource interfaces may include one or more methods of specifying controls for the utilization and/or interaction with resources associated with resource interface. This may include both the resource elements comprising the resource and other resources with which resource may interact. For example this may include specifications detailing responses and/or other actions to be undertaken when resource receives control specifications from other resources and processes.
In common with other PERCos specifications, control specifications may, in some embodiments, include multiple control specification elements, each with appropriate values and/or parameters and/or other specifications, such as, access, identity, rules (for example including types of usage, such as read/write/update/edit/DRM and the like), and/or any other specifications that specify what, when and how resource and/or specifications may be utilized.
Control specifications may specify cryptographic techniques and capabilities.
Control specifications may be persisted, for example through PERCos PIMS, as i-Sets.
In some embodiments, resource interfaces may provide apparatus and method embodiments for separation of those control specifications associated with interactions with the resource interface, and those specifying the associated resources and/or specifications.

Controls for the resource interface of a resource may, for example, specify when and how the resource interface for the resource may be replaced with another interface or when resource interfaces can be added, such as, only authorized invokers may add new methods, and/or only authorized Coherence managers may delete methods. Control specifications for utilizing associated resources, for example, may specify the use of cryptographic techniques and capabilities. For example, control specifications may specify that access to or interaction with certain resource elements comprising the resource be disallowed based on identify of the Participant.
Some examples of the types of control specification elements include, but are not limited to:
Function Description Extend Extends a specification element and replaces the original unexpanded specification element with further specifications. For example, Extend may specify one or more resources that should be used by the control specifications to implement such expansion.
Reduce Reduces one or more specification set elements, making them unavailable for use (transiently or persistently).
Commit Commit a specification element set.
Revoke Revoke a previously committed specification element set.
Select Selects a specification element(s).
Modify Modify specification element as specified by other specifications.
Control specifications may be persisted, for example in some embodiments, as i-Sets by PIMS.
Example control specifications may include the following:
= Authoritative controls that specify rules and/or rights to assign controls individually and/or in control sets (in whole or in part) to one or more other Participants, processes and/or resources.

= Control specifications (including elements thereof) may be delegated, for example where the rules determining the rights to control one or more resources may be delegated to other resources.
= Control specifications may be dynamic such that one or more resources are available and accessible for interaction to any authorized Participant, process and /or resource which can interact with resource interface.
= Control specifications may also be out of band, in that they are expressed implicitly through location and/or physical constraints, such as memory in a portable device may only be accessed by local CPU, whereas the device may have a resource interface for interactions with other devices.
PERCos architecture provides for resources to receive one or more control specifications, which may include specifications of authentication and/or authorization methods, rules and/or other specifications from one or more appropriate controlling resources, processes and/or PERCos Platform Services. In some embodiments, authorization may be, for example, provided using Access Control Lists (ACL), capability-style authorizations and/or other authorization implementations.
In some embodiments, PERCos resources may support one or more authorization features, within which such authorization requirements for the resources are specified.
These features include for example, specifications of resource characteristics (including for example functions), definition of appropriate authorization indicia sufficient to enable other resources to use one or more characteristics, capabilities and/or functions of the resource, and/or authorization and authentication specifications sufficient to permit the authentication and authorization of other resources to use the authorization indicia.
In one example embodiment, a user may establish control over a resource (e.g., initialization of a new laptop computer) through the creation by user of a Participant identity for that user to exercise control over that resource. In this example, user creates a Participant identity, for example "admin" and in so doing creates a persistent relationship of authoritative control over the resources comprising the laptop. These may then be delegated to other Participants, on terms defined by control specifications.
In some resources control specifications may be segmented to apply to only portions and/or sections of resource (and the resource elements thereof), such as a portion of a document, certain tables within a database, a fractional portion of a hard drive (say 10GB of 1TB). For example, in the case where resource element is a set of specifications, control specifications may specify for example, that such specifications may only be segmented such that certain elements (including sets thereof) of the specifications may be interacted with (for example by modification) by certain designated users/resources/Processes.
In some embodiments, access to a particular resource specification (including subsets thereof, such as specification elements/set of specification elements), may be constrained to those resources with appropriate authority, such as, for example, a Coherence manager. This may result in a set of control specifications that are authoritative over each specification element and/or set of elements. For example, access controlled operations may include the ability to:
= receive a request for a change to specifications, = determine if the requested change is permitted, = make the change to the specifications, and/or = provide appropriate notifications to one or more resources as to changes.
In some embodiments, the appropriate authorities may be combined within a common control specification, for example, implemented as differing instances of control functions, and/or maintained as independent functions.
In some embodiments for example, rules and authorities may be specified, such that resource interface specifications may include by reference or embedding the identity of the appropriate control specifications, including for example one or more validation mechanisms that may manipulate resource interface specifications. Alternatively, resource interface may identify control specifications and mechanisms for validating the resulting set of elements returned by control specifications. One such mechanism could enable signing the elements returned by control specifications using the identity of an authorized digital signatory.
For example in a message-based implementation, authority may be evidenced by the right to send or receive messages at a specific message-delivery address (for example a specifically identified resource), or by the authorization to send and/or receive specific message types and/or contents.
In some embodiments, control specifications for resources may constrain various operations on control specification elements and/or resource elements to:
= Appropriate identities (which may include appropriate permission holders, publishers, Participants, processes and the like), = Formal PERCos resources, = Holders of appropriate authority/tokens/credentials, o Which may include "end-user" validation credentials and/or other rules expressions and/or tokens = Anyone with one or more specifications comprising conditions, such as by exclusion, by combination, by appropriate attribute, by obligation, by event, which may include for example:
o A user interacting with resource (and/or arrangement thereof) may view advertising, experience one or more contexts and the like.
o Insertion of further resources and/or experiences generated/represented by resources, which may be managed by Coherence Services, (rather than by, for example, through interruption).
o Provision of avatar (and or other UI representation) generation resource, with mandatory product display in generated avatar/representation.
In some embodiments, PERCos organizational specifications reference those organizations that are associated with the resource, for example the organization of the resource elements that make up the resource and those organizations that the resource itself is a part of. For example this may include resource arrangements and/or assemblies that resource is a member of, as well as class systems, Constructs, directories and/or any other organizational structure (including for example formally unstructured sets, such as i-Spaces (information Spaces), results sets and the like.
These organizational specifications may be formatted and/or modularized to reflect the various organizations to which resource is a party.
In some embodiments, PERCos resource interfaces may include one or more sets of interface specifications. These interface specifications may include one or more suites of methods and protocols for interfacing and communicating between and amongst:
= Resource interface(s), = Resource elements comprising resource, or = Resource interface and other resources, processes and services.
These interactions and communications may include references to one or more control specifications, specifications determining for example data input/output, utilization and access.
The interface specifications may include resource Input and/or Output specifications and their associated methods, such as for fast synchronous data transfers or other performance optimized inputs/outputs.
In some embodiments, interface specifications may include one or more PERCos standardized protocols and/or any resources providing such capabilities. These protocols, for example may be utilized for intra/inter-resource communication methods that allow one or more resources to invoke at least one method of another (including those of the resource elements comprising the resource, if applicable). In some embodiments, protocols may include sets of elements that enable creation, assignation, manipulation, extraction and/or termination of resources and/or their resource elements.
In some embodiments, PERCos interface specifications may include by reference or embeding one or more interface methods, which for example may include communications methods and may utilize associated protocols. PERCos implementations may include one or more standardized sets of methods which may be used by resources.

In some embodiments PERCos may utilize available communication mechanism to embody one or more methods and/or protocols, including procedure call/return, inter-process communication (IPC), remote method invocation (RMI), explicit message queues, blackboards, files, streams, rendezvous, or any mixture of them, provided that all involved resources implement and/or have access to the chosen mechanism(s) for each protocol.
In some embodiments, resource interface specifications may reference one or more suites of such methods and/or protocols. These may then, for example, be associated with a resource such that another resource may use these to access the resource to achieve particular effects. In one embodiment, a process resource may support a protocol suite including two protocols, one protocol for accessing the process locally (e.g., Unix socket) and another for accessing it remotely (SOAP message). A protocol suite may be embedded in and/or referenced by the metadata attribute of the resource, contextually determined, and/or known statically (e.g., because the element is a built-in type of the system, such as integer or string).
In some embodiments, PERCos may include one or more sets of method and/or protocol suites that are standardized and built into the PERCos system. This may both improve efficiency and avoid the possibility of infinite regress (when accessing a method and/or protocol may require accessing at least one or more further methods and/or protocols, some of which may require accessing one or more further methods and/or protocols, and so on, ad infinitum).
In some embodiments, the implementation of some or all methods and/or protocols may be optimized for at least some resources, for example, using PERCos standardized methods, protocols, protocol and/or method caching, constant propagation, code motion, currying, type analysis, and/or other techniques used for efficient implementation of programming languages.
In some embodiments, methods and/or protocols may communicate any set of data/information that PERCos resources may generate and/or receive. This, for example may include specifications of all types, including control, organization and/or interface specifications, from single or multiple resources, and/or other processes, alerts/events, operating agreements, and/or any other PERCos and/or non-PERCos communications.

In some embodiments, PERCos Platform Services may provide communications methods and protocols suites that comprise currently commonly used and available communications methods and/or protocols and/or PERCos specific communications methods and/or protocols. For example this may include the HyperText Transfer protocol (HTTP), Structured Query Language (SQL), Rich Site Summary (RSS), Simple Object Access Protocol (SOAP), Common Object Request Broker Architecture (CORBA), and the like.
PERCos resources may be constructed from one or more elements and at least one PERCos resource interface. In some embodiments, resource architecture may provide a set of operations that enable resources composition and decomposition. It may provide operators such as assemble and disassemble that assembles two or more resources into a single resource and disassemble resources into component resources, if possible.
A PERCos embodiment specification expression is an item that may be interpreted as a specification. A specification is something that any item either does or does not satisfy. The items that satisfy the specification are instances of that specification.
In some embodiments, PERCos embodiments specifications may comprise expressions formulated so as to specify one or more definitions of what may be required to occur when specification is resolved. There are no constraints in PERCos embodiments as to what may be specified, however, for standardization and inter-operability, PERCos embodiments includes one or more specification languages.
In some embodiments, identity can be a form of specification. In some PERCos embodiments anything that can be identified can be specified, as can any resource, however specifications using no standardized terms and specifying those entities without unique identities may not be able to be resolved unless/until appropriate methods for such resolution are provided. PERCos embodiments specifications may be included in one or more specification languages.
Specification expressions may have their interpretation results determined dynamically through one or more operators applied for their use. These interpretations may be persisted. In some embodiments, there are operators, such as prescriptive and/or descriptive that may be applied to specification expressions. Such operators may be included in one or more PERCos embodiments specification languages.
For example PERCos embodiments specification languages may include for example, but not limited to such defined terms as operators, methods, part types, elements, metrics, items, purpose, basic data types and/or other such terms that create an effective language embodiment for instantiations within one or more PERCos embodiments.
In some PERCos embodiments, specification expressions are created and/or selected by a user so as to satisfy that user's purpose, and consequently PERCos embodiments systems may operate so as to resolve such specifications such that one or more resources capable of providing support for user experiences intended to satisfy the user's expressed purpose is made available and/or instantiated. In some PERCos embodiments this resolution is undertaken by PERCos embodiments platform SRO processes.
Some PERCos embodiments include contextual purpose operating environments which may be substantially based on the manipulation of specifications. The expression of purpose by users, in the form of purpose expressions supported by the purpose class systems enables users to define, iterate and/or refine these specifications through their unfolding purpose experiences leading to their achieving satisfaction of their expressed purpose.
PERCos embodiments may also incorporate multiple types of specifications, including, for example, = Purpose specifications = Repute specifications = Resource specifications = Operating specifications = Control specifications = Construct specifications = Coherence specifications = Resonance specifications = Preference specifications = Rule specifications = Role specifications = Class specifications PERCos embodiments use classes as a primary organizing apparatus and method embodiments for specifications.
In PERCos embodiments there may be multiple classifications of specifications into various types. In some embodiments these may include purpose, resource (including Participant), Repute, Dimension, metric and/or any other single and/or multiple schema and/or organizational models.
In some embodiments, classifications may include one or more schemas and/or organizational models for specifications. In some embodiments, such classifications and/or schemas are declarative, such as for example purpose expression, Repute expression, rules expression and the like.
Specifications may be further typed, for example through the degree to which they have undergone one or more processes, including those of their initial expression.
For example class specifications may be typed as "unresolved" as the specific resources have not yet been (in whole or in part) fully identified, whereas specifications that comprise resolved resources would be typed as "resolved."
Declared specification types include for example, purpose, Roles, control, interface, organization, rules, class, Construct, identity and the like, all of which may have one or more other specifications, such as pre and post conditions applied. For example a rule specification may have pre conditions stating one or more specific enforcement methods be applied to such specifications.
Processes types are those specifications that have undergone one or more PERCos embodiments processing. For example those specifications that have had specific processes operate upon them, such as Tests and results service, for example resulting in "validated"
specifications.
Further examples may include such processes as Coherence, resulting in for example "cohered"
specifications.
In some embodiments, specifications may have multiple types expressed, such as for example "resolved, cohered, validated", which in turn may have additional specifications stating the methods (and potentially resources) involved with such type expressions.
In some embodiments, specifications may have further control specifications that determine such type processes (and potentially order thereof) that specifications may undergo. For example such a control specification may include pre and post conditions, which specification may satisfy, such as for example having types such as validated and/or cohered, before further operations with and/or on specification may take place.
Specification classifications may be declared and/or processed.
In some PERCos embodiments, specifications representing for example purpose expressions may be either prescriptive or descriptive. In some embodiments specifications may be declared for use as prescriptive, where they represent what may be required and/or desired by those one or more users. There may be further specifications that are declared for use as descriptive, representing the capabilities, functions, use, applicability, intent and/or other characteristics associated with a resource.
In some embodiments there may be standardized organizations and/or schemas, such as templates that determine specific defined arrangements of specifications. Some examples include, purpose expressions, Repute expressions, Dimensions and metrics, identifiers, information systems and the like. In some embodiments, such classified specifications may for example have rules determining their suitability for such classification and potentially for use and/or dissemination of such classified specifications. In some embodiments, specifications may include dependencies on other specifications, through reference and/or embedding.

In some PERCos embodiments, specifications types may be created through declarations, for example a user/Stakeholder may declare a specification to be a purpose expression. For example one or more resources may declare that a specification is a control specification.
In some embodiments, PERCos templates may provide standardized and interoperable method arrangements by which, for example, Constructs and/or other resource arrangements can be dynamically arranged. For example, through the use of templates, a Construct may develop from a possibly incomplete set of specifications to an operating resource.
In some embodiments, PERCos templates may comprise specifications of one or more resource sets that may be combined and/or used dynamically in an arrangement to satisfy one or more prescriptive specifications. In some embodiments, these templates can be used, for example, to decompose a prescriptive specification into one or more finer grained prescriptive specifications.
In such an embodiment, PERCos processes, such as, Coherence Services may find resources that satisfy these finer grained prescriptive specifications. A template may then assemble these resources into a suitable resource arrangement that, in whole or in part, satisfies the initial prescriptive specification.
For example, a purpose class application may be implemented as a collection of web pages that utilize, for example, JavaScript and Adobe's Flash plug-in. To facilitate the process of resolving the purpose class application into an operating resource, the specification of the purpose class application may include a pointer to a template. This specification template contains instructions on how to resolve the purpose class application into an operating resource if the following resources can be found:
1. A network connection to the internet, 2. A web-browser which includes JavaScript, and 3. The Adobe Flash plug-in.
In this simplified example, when a user selects this purpose class application, perhaps using a double-click if this purpose class application already exists on her Desktop, Coherence processing may try to resolve the purpose class application by looking at the user's Foundation to see if the three resources described above are present. Coherence may also utilize one or more persisted specifications, such for example those of the user that pertain to other Foundation resources, for example stored as profiles, that may include such information as router, firewall, anti-virus, browser settings and if appropriate those further profiles of other Stakeholders, such as corporate policies. If the Foundation contains resources matching these specifications, then Coherence processing can use the purpose class applications template to assemble these resources from the users Foundation into an operating resource.
This example can be continued recursively. For example if the Adobe Flash plug-in is not found in the users Foundation, then Coherence can be called to provision an Adobe Flash plug-in resource as part of the users computing arrangement. An embodiment may choose to include this installer in a template that produces Foundations. The assemble method of this Construct template would be responsible for installing the Adobe Flash plug-in in the users computing arrangement and producing a Foundation that reflects the change that has been made to the users computing arrangement. If the user chooses to associate this new Foundation with his context, PERCos may be able to utilize the user's new Adobe Flash plug-in.
Templates may be specified and/or invoked at any point in the PERCos cycle.
For example, Specification, Resolution and Operational (SRO) Processes may use templates to build, evolve, refine, and/or transform resources into operating resources in a systematic, standardized and/or interoperable manner as described above.
Some embodiments provide Construct templates, which are templates that describe how to assemble Constructs and/or operating resources out of a collection of resources. In some embodiments, users can make use of Construct templates to (1) recursively build Constructs out of other resources and (2) provision and resolve resources to construct operating resources.
Acknowledged Domain Experts and/or other Stakeholders may publish their Construct templates and/or Constructs, allowing others to add, modify, and/or otherwise customize them for their own needs. For example, suppose an Acknowledged Domain Expert publishes a Foundation template. Others may use it to create Foundations, and/or to add to, modify, and/or otherwise customize it to describe their own Foundation Construct templates.

Construct templates may be employed to assemble Constructs, for example without limitation, of the following types:
= Foundation, = Framework, = Purpose class application, = Plug-in, = Transformer/assimilator, and/or = PERCos Identity Matrix (PIDMX).
Some embodiments provide Role templates, which are templates that describe how to assemble resources out of a collection of Roles. For example, a Role template might describe how to create a resource to help a user file taxes online by using a communication role, a processing role and some information roles.
In some embodiments, templates may offer dynamic opportunities to manipulate resources and/or specifications, for example, to provide differing interaction capabilities. For example, templates may supply descriptive specifications of resources before they are assembled. So in some embodiments it may be possible to compare alternative potential arrangements of resources to determine which one would best fulfill a purpose. In addition, if one of the resources in an operating arrangement of resources created by a template is unable to fulfill its operating agreements, then the template can be used to suggest alternate arrangements of resources that would satisfy the same requirements. These are just a couple of examples of how templates might generate multiple differing opportunities, degrees of sufficiency, experiences, dynamic resource relationships, and the like, that are at least in part dependent on a Foundation and/or other resources.
In some embodiments, the methods of a published template are implemented, cohered, validated, tested and successfully operated to an extent that assures that, in appropriate contexts, they can be relied upon to a specified and/or asserted level.

In some embodiments, templates may have one or more associated descriptive specifications.
By performing matching/similarity analysis, a PERCos system may identify one or more templates with associated descriptive specifications that satisfy a given prescriptive specification. Once a suitable template is identified, applying its Assemble method to a suitable set of resources may create a Construct that satisfies that prescriptive specification.
In some embodiments, a template's interface has at least the following four methods:
= Compose, which accepts a tuple of descriptive specifications <DS1, ..., DSk> and returns a single descriptive specification DS.
= Decompose, which accepts a single prescriptive specification, PS and returns a tuple of prescriptive specifications <PSi, ..., PSk>, = Assemble, which accepts a tuple of resources <R1,...,Rk> and returns a resource. The Assemble method may utilize the resource architectures Assemble method during the processing of an Assemble method invocation.
= Disassemble which accepts a resource arrangement created by the template and disassembles it, performing any cleanup as appropriate. This method may need to call the disassemble methods of the resource architecture Templates may supply some of a Construct's resources, including purpose-specific resources, in addition to those passed into the assemble method. These methods may return a failure indication if they cannot complete their work. For example, if a template is asked to decompose a prescriptive specification that it does not know how to implement, it can indicate that it could not create the associated prescriptive specifications.

The methods for a template ST may satisfy the following conditions:
= If, for each i, DS i is a descriptive specification of the resource, R, then ST.Compose (<DS1, DSk >) is a descriptive specification of ST.Assemble(<Ri, Rk>). Compose transforms descriptive specifications of a set of resources into a descriptive specification of their combination by Assemble.
= If <PSi, PSk> = ST.Decompose(PS), and for each i, DS i PSi, then ST.Compose(<DS1, DSk >) PS.
This provides an efficient method of specification-driven resource assembly, i.e., finding a set of resources that may be combined by a template ST to create a Construct that may satisfy a prescriptive specification PS:
= Let <PSi, PSk> = ST.Decompose(PS).
= If Decompose did not fail, for each i, use Coherence or some other process to find a "matching" resource Ri that has a descriptive specification DS i such that DS
i => PSi.
= Let R = ST.Assemble (<R1, ..., Rk>). R is assured to have at least one descriptive specification DS = ST.Compose(<DS1, DSk >) that implies PS.
In some embodiments, prerequisites may be treated separately from descriptive specifications.
For example, a resource may have a prerequisite that it only works with Windows 7 operating system and higher. For such an embodiment, templates may have an additional method for transforming resource prerequisites into Construct prerequisites:
= ComposePre accepts a tuple of prerequisite specifications <PR', PRk> and returns a single new prerequisite specification, PR.

ST. ComposePre should satisfy the condition that if, for each i, the prerequisite specification of is PR, then the prerequisite specification of ST.Assemble (<R1, ..., Rk>) is PR.
Thus for example, a Construct template may decompose the problem of accessing a web page on a private network into two requirements: a working VPN to the private network and a browser with sufficient capabilities to view the web page. The VPN solution found may have a perquisite specification requiring a credential to access the private network and the web page may have one that can only be viewed on Internet Explorer. So the composed prerequisite specification may require a Windows platform with Internet Explorer and sufficient credentials to access the private network.
In such an embodiment, the method of finding a set of resources that may be combined by a template ST to create a Construct that may satisfy a prescriptive specification PS given a Foundation, F, may include some additional parts as follows:
1. Let <PSi, PSk> = ST.Decompose(PS).
2. If ST.Decompose did not fail, for each i, find a "matching" resource Ri that has a descriptive specification DS i such that DS i => PSi.
3. If PREQR1,...,PREQRk are the prerequisite specifications for the resources R1,...,Rk then calculate PREQR=ST.ComposePre(QR1,...,PREQR0.
4. Verify that the prerequisite specification PREQR is met by the supplied Foundation, F.
For example, if the prerequisite specification, PREQR, states that the assembled resource may only work on a Linux platform and the Foundation specifies only a Windows system, the caller should reject this proposed assembly. If the prerequisite specification is not acceptable then go back to part 2 to find an alternative collection of resources that can be used.
5. Let R = ST.Assemble(<Ri, Rk>). R is assured to have at least one descriptive specification DS = ST.Compose(<DS1, DSk >) that implies PS.
6. Associate PREQR as the prerequisite specification for the resource R.

Some embodiments may provide one or more languages for the specification of new templates, including templates that generate further templates. These may be in a variety of styles, for example and without limitation:
= Scripting languages, in the manner of, for example, JavaScript, Unix Shell, DOS
Command Shell, and the like.
= Markup languages, in the manner of, for example, XML, HTML, and the like.
= Diagrammatic languages, in the manner of, for example, Visual Basic, and the like.
Some embodiments may provide one or more templates for supported specification languages that convert individual specifications in those languages into corresponding templates.
Foundation templates are PERCos templates to assist users (including experts and Stakeholders) in specifying their Foundation resources. In some embodiments, they may specify one or more standardized resource arrangements to support one or more operating Constructs and purposes based on and/or including user preferences and interfaces. They may also specify Foundation elements that users may need to provide to describe their foundational resources, such as, their operating environment, such as contextual usage characteristics, performance specifications, or other parts of the operating environment. Foundation templates may assist users with governance specifications that specify rules for supporting Foundations.
Some embodiments may utilize prescriptive and descriptive Foundation templates. A
Stakeholder creating a Construct or other resource may, directly or indirectly, use a prescriptive Foundation template to specify Foundation requirements for using her new resource. For example, an embodiment might provide a purpose class application to help develop Foundations. A user writing a web application could interact with this purpose class application to specify that the Foundation may require a modern browser (e.g., a browser that can handle HTML 5 and JavaScript). The purpose class application might generate this Foundation by starting with an empty Foundation (that does contain any constraints) and applying a Foundation template that adds the modern browser. Similarly, if at a later time the user finds that his Construct or other resource may require other technologies such as Adobe Flash, the user can interact with purpose class application causing it to apply a Foundation template that adds Adobe Flash to the Foundation.
In some embodiments, by using Foundation templates in this way, the purpose class application may support interoperability and Standardization. If the Foundation templates are created by acknowledged Domain experts, then the PERCos embodiment may not get cluttered with different ways of specifying the same requirement such as "latest Oracle Java", "Sun Java", "Java 1.7.0_06", "Java 7", or the like. A standardized collection of Foundation templates may utilize a common and interoperable scheme for representing this requirement.
In some embodiments, by using Foundation templates in this way, the purpose class application may detect conflicts. For example, suppose that a user starts by specifying a Foundation of Apple iOS (e.g. she is targeting an Apple iPhone or iPad). Then if she adds a requirement for Adobe Flash, the Foundation template that adds Adobe Flash may be able to look at the existing Foundation and determine that Adobe Flash is not compatible with i0S.
Some embodiments may permit users to use descriptive Foundation templates to refine a Foundation describing their system. Thus for example, a user who has recently installed a new version of Java in her computing arrangement may have a Foundation that does not yet specify this new Java capability. This user may invoke a Foundation template that compares the users Foundation with the users computing arrangement and provide an updated Foundation that creates a modified Foundation that removes old functionality that is no longer present and includes any new features that it finds. This Foundation template might interact with the user when generating the new Foundation so that the user can override any decisions that the Foundation template makes. For example the Foundation template might find that a certain feature appears to be missing, e.g. a graphic card capability, when this feature is only temporarily inactive (e.g. it may be restored on the next boot).
Foundations may be published as templates, in part or in whole, and further comprise specifications and/or instructions that vary their respective usage, for example, Foundation characteristic expressions (in some embodiments these may be resource characteristics specifications, as Foundations and Foundation templates may be resources), such as specialized Foundations for supporting tax preparation, video editing, and/or other PERCos process and/or operations.
Foundation templates may be extracted and/or derived from operating Foundations. Such templates may be made persistent through use of appropriate publishing services, such as PERCos Platform publishing services, over the course of operating Foundation session operations.
Foundation templates, like any other resource, can be published and/or associated with one or more purposes. They may also utilize history or other storage mechanisms to, in whole or in part, store the unfolding specifications, and such stored template specifications may then be made available to one or more process, subject to Governance, potentially for in one embodiment, publication and further distribution.
In some embodiments, purposeful templates (PT) may be used to create, build, and/or instantiate purposeful Constructs, such as, Frameworks, plug-ins, purpose class applications, resource assemblies, and/or other PERCos objects that can be evolved, cohered, resolved, and/or transformed into operating Constructs.
Users and/or acknowledged Domain experts may create purposeful templates for use by other users to create, build, and/or instantiate purposeful Constructs in pursuit of their respective purpose experiences.
Purposeful Templates (PT) may be associated with one or more purposes and can support differing degrees of purpose generality. Some PTs may be highly general and may require users to refine them before they can be transformed into purposeful Constructs. For example, acknowledged Domain experts may provide a general template that other users can customize as appropriate to arrange resources for efficient and effective pursuit of their respective purpose experiences. Suppose a professor created a highly general PT, GenMusic that enables a wide range of users, from music students and amateurs to professionals enabling them to use/build/create Frameworks for learning about classical music. A user may use this purposeful template to create and/or build a Framework that enables professional musicians to prepare for their performances.
Like other Constructs, purposeful templates can be specified at varying degree of completeness.
Users may need to provide additional information, such as, additional resources before a purposeful template can be used to build/create Constructs for fulfilling purposes. For example, a purposeful template may provide specifications for providing purposes, such as, specifications for purpose expression elements, such as, Master Dimensions, user preferences, and the like.
However, it may not have the structural specification to organize resources.
In such a case, users who wish to use the purposeful template may need to apply a template to provide the structural information before they can use it to create new Constructs, such as, Frameworks.
Framework templates are templates intended to assist users to create, build, and/or instantiate Frameworks. In some embodiments, they may specify standardized resource arrangement for multiple purposes based on and/or including user preferences and interface.
They may also specify Framework elements that users may need to provide so that they can be processed, transformed, and/or evolved to generate control specifications, organizational specifications, interface specifications, metadata, and the like. For example, Framework templates may assist users to specify, = One or more purposes and/or purpose operations.
= Values for Master Dimensions, auxiliary Dimensions, and the like.
= Foundational dependencies, resource functionality and/or capacity, governance, for example based on one or more forms of authorization and/or authentication and including one or more rule sets or other governance process and/or operations.
Framework templates may be used, subject to governance processes, in multiple Contexts, including those for which their creator may have no knowledge and as such their specifications may be varied, through Coherence Services, to suit the applicable resources and/or Foundation arrangements.

Frameworks, plug-ins, purpose class applications, resource assemblies, and/or other PERCos objects may be published as templates, in part or in whole, and further comprise specifications that vary their respective usage, for example, Participant characteristic expressions, such as "Learn"rBeginner"rCategory N", and/or other PERCos process and/or operations.
Framework templates may be extracted and/or derived from operating Frameworks.
Such Framework templates may be made persistent through use of appropriate publishing services, such as PERCos Platform Publishing Services, over the course of operating Framework session operations.
Framework templates may also utilize history or other storage mechanisms to, in whole or in part, store the unfolding specifications, and such stored template specifications may then be made available to one or more process, subject to Governance, potentially for in one embodiment, publication and further distribution.
A resonance template comprises a set of algorithms associated with one or more purposes for enhancing resonance (e.g., optimizing and reducing friction) of results sets.
In some embodiments, there may be a variety of resonance templates. Some examples, without limitations, are as follows:
= resonance experience templates, and/or = resonance result templates A resonance experience template may comprise a published specification template that contributes to a purpose-related operating session results in an experience that resonates with the user. For example, suppose a user is interested in learning about thin film solar cell technology.
A resonance experience template may support users to obtain purpose experience that resonates most with the user. In some embodiments, a resonance experience template may support a variety of resonance templates, such as, resonance experience templates, resonance results Frameworks, and the like.

In some embodiments, resonance experience templates may support users with the optimization of the quality of purpose experience, such as, the quality of unfolding process, purpose operations, and the like. For example, suppose a user is interested in listening to a piece of music. There may be many ways (purpose experiences) for the user to hear the same piece of music. A resonance experience template may provide methods for the user to obtain most pleasant experience, where pleasantness may be due to the ease of obtaining listening experience, the medium for providing the music, and the like.
A resonance result framework may enable users to efficiently and effectively create, structure, build, and/or organize one or more arrangements of resources in pursuit of purpose experiences that focus on optimizing different aspects of purpose results. For example, commercial result frameworks may enable building and/or creating one or more arrangements of resources for fulfilling purpose experiences that produce commercial results that resonate most with users.
Suppose, for example, a user is interested in exploring in finding a decorator who can redecorate their house. For example, a commercial result framework may provide apparatus and methods to structure, aggregate, organize, and/or arrange resources for producing a list of decorators who would most resonate with the user. For example, even though there are two decorators who are equally skilled and have the equivalent Reputes, the user may resonate more with one decorator's customer interaction style than the other.
Some embodiments may provide different types of resonance result Frameworks depending on the type of results, which may include for example, without limitation, the following:
= Commercial, = Organizational, and/or = Knowledge/Structured information.
Templates, like all resources, may have associated resource characteristics and/or descriptive specifications, Reputes, and/or other metadata to assist users in support of purpose fulfillment.
Templates may additionally have associated specifications that indicate appropriate resources, tools, and/or guidelines. For example, they may provide users with navigation and exploration tools, purpose class applications, and the like, that users can use to complete them, such as:
= Control specifications specify operations of resources that are combined into a Construct and may include, for example, purpose operations specifications, navigation and exploration control specifications, and/or purpose formulation control specifications.
They may be used in the control and management of varying, and potentially very large, resource arrangements.
= Organizational specifications specify organization and arrangement of component resources that comprise a Construct and may include specifications for one or more purpose organizations.
= Interface specifications specify interface characteristics that may be accessed and/or interacted with by other resources, such as resource Roles. In some embodiments these may be standardized PERCos resource interfaces with associated interface specification sets, and may include operating agreement specifications, which express and determine interactions between a Construct and other resources and/or interactions among resources comprising the Construct.
In some embodiments, some or all of these associated specifications may be resources passed to a template, along with component resources, when it is invoked.
Some PERCos embodiments may provide specialized templates that assist users and/or acknowledged Domain experts in efficiently and effectively arranging appropriate resources for the pursuit and/or satisfaction of purposes. These organizations may be based upon one or more principles, which may involve standardization, Dimensions, Reputes, and/or other specification sets. In some PERCos embodiments, some templates may invoke PERCos Platform services, and/or include such invocations within the methods of the Construct.
As illustrated in figure 18, is an illustrative example of a simplified resource created as a Construct instance..

In some embodiments, some Constructs, such as certain purpose class applications, may have constituent specifications and resources that have been previously cohered and resolved, so that these Constructs are ready, once coupled with their prerequisite resources, to be launched as operating resources. Other Constructs may require further processing, for example, cohering and/or resolving, before they can be launched as operating resources.
Many operating systems are based on complementary notions of computational units (e.g., tasks, processes, threads) and storage or communication units (e.g., files, streams, pipes, memory).
However, this distinction cannot be consistently imposed in a platform independent system.
Storing and retrieving information involves computation, and computation involves storing and retrieving information. Similarly, communication may involve any or all of storing, retrieving, and computation. A distributed operating environment inherently involves communication. In a well-structured distributed operating system, requesters may not know (and may not care) where, when, and to what extent such storage, retrieval, computation, and communication take place. (Caching is a very simple example of this.) Hence, PERCos embodiments treat them all as resources.
An aspect of platform independence is standardization of messaging (including communication protocols) and resource method suites. PERCos embodiments systems may embody any or all of the following kinds of standardization:
= Types, data formats, and methods embodiments may be precisely specified.
= Types of organizations and/or information structures and patterns may be precisely specified.
= A set of agreed communication methods and/or protocols.
= Apparatus and method embodiments for "self-describing messages" (messages that contain information on how to interpret them precisely) may be employed.
= Out-of-band information (e.g., knowledge that the invoker is a resource running on the same (or the same kind of platform) may enable optimizations.
= A precise syntax and semantics for purpose expressions (including CPEs) may be specified.

= Resources may retain their relationships with other resources = Other de facto and de jure standards, including dictionaries and ontologies may be used.
The goal of standardization and interoperability is to ensure that each invocation of a method of a resource is properly interpreted, i.e., it carries out the relevant operations to generate and return specified results and change state as specified.
Existing information systems largely operate as "silos," where particular applications and tools are intimately bound to particular data formats, storage mechanisms, data locations, communication protocols, and/or access control regimes, locking in users and may render "connecting the dots" excessively difficult if the dots happen to be in different silos. The applications supported by such systems are largely comprised of sets of specific functions that perform particular application-specific tasks. By requiring the user to choose one (or a few) silo(s), they obstruct the user's ability to organize available resources to supply customized services, shaped to the specific current user purpose(s). PERCos embodiments free users from preconfigured task silos, allowing them to employ resource capabilities and dynamic arrangements that are optimized for fulfilling specific user purposes as indicated by CPEs, context, and history.
PERCos embodiments systems may provide access to resources that have been traditionally linked in silos. Legacy silo applications can be embedded in PERCos embodiments resource arrangements, such as for example Constructs including Frameworks and Foundations or otherwise integrated into resources. Preferred embodiments may, over time, encourage external to PERCos silos to adopt a more flexible and eclectic approach for deploying and using tools and data resources.
A PERCos embodiment resource architecture may emphasize platform independence, using each resource by invoking its methods¨often independent of its implementation or location. A
resource may operate on different platforms or platform variations and may produce different results for different users, because, for example, the users have access to different resources, have different rights, and/or have differing purpose specifications. PERCos embodiments systems may interface with "legacy" or other platform-dependent systems through specialized method implementations called transformers; the properties of a transformer may be constrained by platform dependencies built into the underlying resource.
On the computing side of the Edge, there may be multiple information organizations, comprising multiple sets of resources and/or information about those resources. In some embodiments, these information organizations may be closely coupled to the information itself, such as for example databases, directories and/or other information repositories. Information organizations may have purpose expressions associated with them, for example descriptive CPE, and may be associated with one or more purpose class systems.
One key aspect of the information organization in some PERCos embodiments is the relationships of resources to each other, which happen to be independent of any of the organizational structures that they may be associated with. These resource relationships enable one or more resources to be configured into information organizations that can effectively be matched and/or manipulated to meet users internal information organizations (user classes), initially through class systems and thence through semantics, syntax, linguistic and/or other algorithmic organization constructs.
The flexibility of this approach through the minimal organizational overhead of classes provides users with the apparatus and method embodiments to arrange both their own purpose on the human side of the Edge and the computer domain results sets, so as to achieve an optimized, for that user in that context with that purpose at that time, degree of purpose satisfaction.
In some embodiments, this organization of information on the computing side of the Edge may be considered as an information matrix, comprising those organizing principles, such as for example classes, complemented with those results sets that users, processes and/or other methods, such as for example Coherence, have represented. This information matrix may then be manipulated and managed by users to suit their own purposes and/or associated perspectives.
These manipulations may be derived from their initial purpose expressions, and may span multiple purpose Domains as, for example, users absorb the results and iterate their purpose in response to those results sets.

In some PERCos embodiments, these information organizations may be constructed by experts, reflecting the "best practice" and/or commonly accepted organizational structures for those purpose Domains that encompass their expertise. This may include multiple information organizations representing differing perspectives and/or presentations of resources comprising those domains.
Users may also create, manage and/or manipulate their own information organizations in manners that suit their context and/or purposes. For example users may choose an ontology organization for a large information set, that they maintain in a cloud storage environment, and a more simple single index based organization in a constrained computing environment (for example a mobile device).
Users may also store their information organizations for reuse by themselves and/or other users.
Such organization can be published as a PERCos resource set for use by wider user constituencies and its creator and/or publisher, through, for example, Reputes, may over time become considered to be experts in their domain of purpose publication.
In some PERCos embodiments, resource relationships may be used by processes, and/or resources (including specifications) and/or one or more users/Stakeholders to create information organizations that satisfy one or more purposes.
These resource relationships may comprise any specifications that express the relationships, which may for example include metrics, class membership, indexing, database relationships, set memberships, attributes and/or the like. PERCos embodiments, in dealing with the one-to-boundless may also have defined relationships which may be used in a standardized and interoperable apparatus and methods embodiment to support purpose operations.
Some of these standardizations include:
= Class systems = Ontologies = Purpose expressions = Purpose specifications = Resource characteristics specifications = Repute expressions = Categories and verbs = PERCos embodiments repositories = PERCos embodiments similarity and matching systems = PERCos embodiments publishing systems = PERCos embodiments Platform Services In many circumstances the effectiveness of these capabilities in creating information organizations and resource relationships with high degrees of utility for the satisfaction of purpose may be determined by the degree of expertise of the users who have utilized these capabilities. For example an expert in purpose Domain 1, may create a specific set of specifications, that when fully resolved, provide users with limited or no expertise in Domain 1, an environment in which they may obtain an appropriate set of resources sufficient to satisfy their purpose.
PERCos embodiments provide the apparatus and method embodiments for experts to leverage their expertise to the benefit of users and provide them with the ability to express their expertise in one or more purpose Domains.
Resource relationships may be stored and manipulated and/or published as resources for use by one or more users.
PERCos embodiments enable resource relationships to be organized in any manner one or more users may elect, however, should that election not include the standardized and interoperable capabilities outlined above, such organizations may be of little value in satisfying purpose.
PERCos embodiments capabilities encourage users to utilize the standardized and interoperable PERCos apparatus and method embodiments to satisfy their purpose and provide such satisfaction expressions to other users with the same or similar purpose intentions.

In some PERCos embodiments, a user has an associated information space that is particular to them, in that it may comprise the information sets generated by their interactions with PERCos embodiments resources and/or information sets. These sets of information provide users with the opportunity to manage their PERCos embodiments interactions.
In some embodiments, the organization of sets of resources and/or information by one or more experts may be represented through one or more standardized and/or interoperable PERCos embodiments apparatus and method embodiments, including for example class systems, Constructs, class and/or purpose applications, purpose plug-ins and the like.
Experts may select the degree to which user interactions with their PERCos embodiments representations may be controlled by one or more sets of specifications.
Experts may publish their resources, specifications and information sets.
In the computational domain, information may be organized in any manner however such organizations generally have an intention behind the organization principles for the formatting of information into a knowledge structure. For example these may be used for knowledge storage, representation, transfer, interaction and/or other associated processes. Currently examples of knowledge structures include Logics, Databases, Directories, and the like.
Generally such current knowledge structure implementations have close associations between the information organization, the schema, and the utilization of that knowledge (often including the representations, such as for example forms and the like) and/or the processes for interaction with the knowledge contained therein (for example SQL) PERCos embodiments may provide multiple organizations of information into one or more knowledge repositories, enabling users to interact with such repositories in pursuit of their purpose. In some embodiments, these organizations include class systems, purpose Domains, Repute repositories and other knowledge structures that are aligned with the purposes with which they are associated.

Currently there are a number of knowledge structures that provide general information and knowledge management systems such as for example, Wikipedia, DMOZ, Semantic web, Encyclopedia(s), dictionaries, thesaurus, any reference systems including classification schemas such as ISBN, Dewey Decimal, Library of Congress and the like. There are also specialized portals providing sets of knowledge. However none of these provide purpose metadata, nor are they organized by purpose.
In many circumstances the expression and communication of knowledge may require one or more standardized knowledge repositories and communications methods for such knowledge transfer.
PERCos embodiments may include one or more methods embodiments, including through one or more classes as embodiments of information organization for purpose operations, for example providing a lossy apparatus and method embodiments for such operations.
In some embodiments, Classes, as an organization may be used to express purpose, resources, attributes, modalities, temporalities, combinators, synonyms and the like.
In some embodiments, PERCos embodiments may include one or more ontologies for purpose expressions and/or operations. Such ontologies may be created by one or more experts, which may also have associated Reputes indicating the standardized and well accepted nature of an ontology within a given purpose Domain. For example, purpose Domain ontologies may comprise those resources and/or information sets regarding those resources that are associated with one or more sets of purposes (potentially expressed in one embodiment as purpose classes), whose relationships have been specified/defined as sufficiently consistent and/or have been to be declared, by one or more Stakeholders to be members of a given class structure (including sub classes and/or other class relationships).
In some PERCos architecture embodiments, a key aspect is the expression of relationships among purposes, resources, users/Stakeholders and any other specifications comprising a purpose system. These relationships inherently provide the basis for multiple systems including, for example, organizational, categorical, algorithmic and the like to create and derive the rich diversity of possible experiences that may be generated as users pursuit of purpose unfolds.
Another aspect of PERCos embodiments systems is the satisfaction, to the optimal degree possible, of users' purposes. In some embodiments this involves two primary apparatus and method embodiments for undertaking such optimizations, Repute, which identifies and expresses the quality of one or more resources to purpose, and resonance which expresses the optimal resources (and arrangements thereof) for purpose.
Management and alignment of these resource relationships may be driven by user purpose and their associated interests and expertise. However when multiple such purposes and/or resources are involved, they may be either inconsistent and/or incomplete and may be coordinated by Coherence services. In some embodiments, Coherence services algorithmically formulate new specifications based on the totality of contextually-related specifications.
An optimal Coherence embodiment does not normally require a particular source or the form of specifications. Such a bias-free architecture accommodates a broad array of differing synergistic functional subsystems.
PERCos embodiments systems may provide apparatus and method embodiments for one or more users to convey their purpose across the Edge in the form of purpose expressions and for PERCos embodiments system to manage, arrange and deploy applicable resources for user purpose with the objective of providing an appropriate purpose results set.
Throughout this process relationships between these purpose expressions, user representations and cross¨Edge resources become established.
Human-understood purposes may be closely related, for example "get" and "buy"
may be understood similarly by the human. PERCos embodiments provide apparatus and method embodiments for representing relationships among purposes as well as other resources. For example relations may be represented though class systems, Dimensions, metrics and/or shared resources. Such relationships may be declared by one or more users (including experts) and/or derived from historical information.

In some embodiments, users/Stakeholders (and associated Roles) may declare one or more sets of interests and/or expertise in various domains, which may be expressed to a greater or lesser degree and also may indicate the degree of interest and/or level of expertise.
For example a user who has a degree in sociology, may additionally have expertise in technology, intellectual property and wine appreciation. In some situations, such a user, when for example pursuing their wine appreciation, may wish to converse with others who have similar interests, so as to for example, satisfy their expressed purpose, of finding mineral toned Chardonnay at an acceptable price point. For this purpose they may wish to dynamically interact with other wine appreciators of a similar level of expertise, rather than depend solely on experts.
In many social situations, users may not wish to have their expertise compared and/or related to experts, for fear of seeming to have no or little appreciable social value.
Experts may form committees and/or other informal or formal groups to discuss, arbitrate and/or further develop their domain expertise. In many of these cases, there may be specifications (often as rules) determining the membership of these groups. Such expert groups may undertake the development of new standards as well as maintenance and/or auditing of existing standards of the domain of their expertise.
The relationships between experts may influence the apparatus and method embodiments and methods for the publication and distribution of expertise that groups of experts have developed.
Stakeholders may have relationships amongst themselves that may be commercial or non-commercial, such as for example Patent Pools, distribution arrangements, delegation of responsibility and the like. In some embodiments, these stakeholder relationships may form purpose domains for example DVD consortium, Open Source Foundation and the like and may incorporate one or more organizational structures.
Roles may include one or more sets of specifications that determine the relationships and degree of interaction of Roles with other Participants.

PERCos embodiments may provide apparatus and method embodiments and methods for creating such dynamic social interactions based around one or more purposes (including common purpose), with appropriate expertise selection and definition capabilities, and further providing for such groupings to be formalized (and/or published), persisted and/or made into further PERCos embodiments resources.
Human, as well as computer, behavior always has context. In PERCos embodiments there are both standardized, and other, sets of contextual information which can be represented cross-Edge, by users, publishers, and/or other Stakeholders for use in and by a PERCos embodiments computational domain.
PERCos embodiments may provide apparatus and method embodiments to systematically frame and convey facets of users' purposes in contexts that can be interpreted to generate appropriate operational specifications for such purpose operations in such contexts. A
PERCos embodiments system enhances human/computer evaluation, organization, management, interpretation, and presentation of contextually available resources so as to optimally satisfy users' purposes.
In some PERCos embodiments there may be one or more processes, for example Coherence, Repute, SRO and the like that assist in dynamically resolving these contextual specifications into sets of resources that can be further resolved into operating resources forming cohesive and efficient operating sessions in pursuit of unfolding purpose operations leading to appropriate contextual user experiences.
Such dynamic resolution of specifications in support of interactions for user experience across the Edge is provided by an integrated PERCos embodiments environment, which includes for example, inter alia:
= Resource and/or information management though for example classes = Platform services that include appropriate sub-systems for purpose operations = Coherence services that resolve inconsistencies and incompleteness = Repute systems that provide credibility metrics and evaluations = A scalable service-oriented resource architecture for purpose operations = Specification languages and representations, including those for expression of contextual purpose All of which combine to provide, in some embodiments, users with apparatus and method embodiments to resolve their purpose expressions so as to generate cross-Edge experiences that in whole or in part satisfy their purpose.
A PERCos embodiment may provide a specification-driven, adaptive dynamic environment.
Rather than merely supplying applications suitable for pre-identified general activity types (word processing, spread sheet, accounting presentation, and the like), a PERCos embodiments environment is designed to provide experiences corresponding to expressed contextual purposes by generating resource arrangements and unfolding executions in response to specifications including purpose expressions.
For example, PERCos embodiments environment may provide users with iterative and/or interactive sets of processes, including for example PERCos embodiments Platform SRO service (Specification Resolution Operational), for assisting users in specifying their Contextual Purpose Expressions (CPEs) so as to generate operational specifications that may lead to satisfactory user experiences.
This rich environment may include knowledge discovery tools that users may use to discover and/or manipulate knowledge captured and published from past experiences by other users, Stakeholders and/or systems. It may also provide specification languages, services, tools, and/or utilities that users, Stakeholders and/or systems can use to compose and/or build and/or otherwise manipulate knowledge structures. Such structures may be used to articulate and subsequently identify and/or prioritize rich, nuanced, and highly responsive specifications and their associated resolutions extracted from arbitrarily huge resource arrays for user contextual purpose operations.
In PERCos embodiments anything can be a resource. In some examples a resource may be a book, comprising chapters. In this case should a chapter be extracted from the book (described as extracting a "facet" from a resource), and given an identity, then such a "facet" would be a PERCos embodiments resource element, which can be a type of PERCos embodiments resource.
Such an element could then be combined with other resources and/or associated with one or more resource interfaces to create another PERCos embodiments resource.
Facets may be created by any apparatus and method embodiments, declarative, algorithmic and/or by any other methods, limited only by resource set from which facet may be extracted to support such an operation. In the example above, the information structure (chapters) provides an apparatus and method embodiment to which an extraction method may be applied. Whereas if the resource was, for example, a "black box" process (for example a java .jar or dll), whose resource interface declared the resource as base, then a Facet could not be extracted.
In some embodiments, this degree of resource composition and ability to have further facets extracted may be defined by appropriate resource interfaces, and as such where a resource is declared as base, with no potential to extract any underlying components of resource, and complex, where there may be potential to extract facets from resource.
In some embodiments, where resources comprise complex arrangements, extraction of facets may be undertaken by employing methods that involve multiple algorithmic calculations. For example multiple candidate results sets may be processed through purpose operations, comprising multiple resources and associated information. PERCos embodiments platform services may provide a facet extraction capability, which under command of appropriate specifications (PERCos embodiments control specifications), may operate on such results sets so as to extract appropriate facets, which may then, for example be composited into one or more other resources, which, may in turn be utilized in further purpose operations and/or published.
3 Classes Class, subclass, and class system are key concepts of PERCos systems. This disclosure about PERCos classes introduces and discusses some of these aspects, with a focus on their use to specify and/or manipulate purposes and/or resources.

The concept of class is important in organizing, describing, and/or reasoning about the relationships among many kinds of things, including human activity requirements and resources for responding to them. Class- and subclass-based categorization and reasoning are older than Aristotle ("All Men are mortal. Socrates is a man. Therefore, Socrates is mortar), and probably nearly as old as language itself. Classes are inherent to human thinking and context, and constitute a practical lynchpin of human relational perceptions of reality.
PERCos embodiments augment class structures and relations beyond the capabilities traditionally provided in class-based applications such as Object Oriented Programming (00P). Its more general relational and weighted structures facilitate, among other things, efficient approximate searching, matching, and reasoning operations.
Classes are a very broad notion, useful for a variety of purposes. That very versatility can make discussions of the uses of classes confusing, unless the uses are carefully distinguished. Later sections describe certain important aspects of PERCos systems in terms of various class systems. In some embodiments, some of these class systems may share some or all of their data structures and operations, and some class systems may contain class Subsystems of multiple types, including, for example, purpose classes, resource classes, publisher classes, and asserter classes.
It is the nature of reality that most tangible and conceptual things cannot be described comprehensively and with absolute precision. Nor is it practical to give a distinct name to each possible thing. Properly used, classes can provide powerful practical solutions to both of these problems.
The name of a class of similar things (e.g., "Human," "Star," "Country") makes it possible to generally and practically refer to this collection of related items, without any need to list them all. Inclusion in a class allows the possibility that some members have further attributes making them members of one or more subclasses, to as many levels of detail as are appropriate. For example, "Human," "American," "Californian," "Female," "19th Century," ...

The usefulness of a class or attribute in discourse depends in part on the degree to which it corresponds to similarities and/or distinctions that participants recognize¨in certain contexts¨
and the ease with which those users inherently and/or explicitly recognize their correspondences with class/attribute names. Thus a child's cosmology might consist of "Sun,"
"Moon," "and Star," while an astronomer's might include "Star," "Planet," "Planetoid,"
"Moon," "Asteroid,"
"Comet," "Galaxy," "Nebula," "Black Hole," or other astronomical body. Such collections of names are often organized, codified, and/or presented as taxonomies or ontologies.
Examples of pragmatic aspects for a taxonomy are, without limitationõthat it be:
= Complete: Each pertinent item is included in a class in the taxonomy.
= Classification consistent: No pertinent item has more than one most-specific classification.
= Perspicuous: Those knowledgeable in the domain may easily map between their conceptual structures and those of the taxonomy.
= Generalizing: Each class groups items and/or subclasses that have enough attributes in common to support useful general statements about the class.
= Discriminating: Distinctions that those knowledgeable in the domain might wish to make can be expressed using one or more classes and/or attributes.
= Practically Simplifying: The taxonomy records the most important/practical characteristics of the items being classified, but omits much less-useful detail.
An ontology may generally relax conditions, and allow some items to belong to multiple classes that are not necessarily hierarchically related, and may also generally define relations among classes in addition to subclass/superclass.
When a name of a member is replaced by a name of a containing class, information is generally lost (e.g., "Athenian" is a less-precise reference than "Socrates," because there are members of "Athenian," that aren't "Socrates.") Similarly, when a name of a class is replaced by a name of one of its superclasses, information is generally lost (e.g., there are more members of "Greek"

than of "Athenian.") Such replacements by class and/or superclass names are useful examples of lossy transformations.
In some embodiments, if a transformation loses information substantially relevant to a current purpose, it may be undesirable¨we might start out, for example, with the purpose of learning about the philosophy of "Socrates," and be given all the "Greek" philosophies instead. But appropriate lossy transformations add value by preserving essential information and discarding irrelevant information. They are among our most powerful tools for capturing, structuring, storing, searching, and otherwise managing useful summaries of information.
They can help organize a vast quantity of items and their characteristics that constitute a domain of interest¨if our purpose were looking for information about the army in which "Socrates"
served, the class "Athenian" would probably be a better starting point than its member "Socrates." The challenge is to find and use the right lossy transformations at the right times and in the right contexts. This is discussed in following sections. Other name replacement processes may add or otherwise enhance information.
Class lossiness corresponds to the nature of much human thinking, by serving as conceptual, impressionistic arrangements that are inherently flexible. They support co-evolution of human and computer reasoning and assist progress towards purpose satisfaction.
Traditionally, classes provide a framework for describing structures relating sets of items (or objects). Each class has a set of items that are its members (instances), which share particular attributes (fields and/or methods), but may differ in other attributes. An attribute may be referenced by names and may either have a value or be abstract (not yet specified). Methods are operations that access a member, for example, to set, modify, change, and/or extract the values of one or more of its attributes. Fields are non-method (value) attributes.
Properties are Boolean fields. Within such structures, class names provide a way to identify (designate) class specifications, enabling them to be used "by reference" without repeating their full specifications.

Some classes may be statically defined, while others may be dynamic, e.g., arising in the course of a computation.
Three common ways of specifying a class are the following:
1. Specification by properties: By declaring the attributes that may be required of each member.
2. Specification by enumeration: By listing its members.
3. Specification by reference: By providing one of its names.
The first two forms are useful for specifying new classes; the third, for reusing existing class specifications.
A class system is a set of classes, together with at least a subclass relation over them. The classes in a class system may be related in a variety of ways. However, subclass is the fundamental relation used to relate classes in traditional class systems. A is a subclass of B (and B is a superclass of A) if all members of A are members of B. This implies that each member of A has at least the attributes that all members of B have.
Three key ideas of class systems are:
1. The members of a class are items related by sharing certain attributes, possibly with restrictions on their values.
2. Subclasses inherit (share) the attributes (and restrictions) of each of their superclasses.
3. Classes provide a method to consider their members collectively, rather than one at a time.
The concepts of subclass and member should not be confused. TallBox might be a subclass of Box, meaning that all its members are members of Box, but this subclass would not be a member of the class Box. i.e., any member of TallBox would be a member of Box, but the class TallBox itself would not be (nor would the class Box).

In some embodiments, Class specifications need not be written from scratch:
Existing classes, identified by their names, can be combined and/or extended to succinctly specify new classes. A
compact way of describing a new class is to list one or more superclasses and add any further attributes that all members of the new subclass have.
For example, a class Box might have the attributes height, width, and depth.
= PaperBox might be a subclass of Box, with the additional attribute material with the value paper, and the additional method flatten.
= TallBox might be another subclass of Box with the additional property tall indicating that its height is more than twice its width.
= WideBox might be yet another subclass of Box, with the additional property wide indicating that its width is more than twice its height.
= TallPaperBox might be a subclass of both TallBox and PaperBox; this description is equivalent to "the subclass of Box with the additional attributes tall, and material (which has the value paper), and the method flatten."
For example, as illustrated in figure 19, a simple class system is shown.
Figure 19 represents an example class system. i.e., where there is enough contextual information to interpret terms in sufficiently similar ways. This class system is particularly simple, but is sufficient to illustrate a number of points about class systems and their traditional uses.
Classes are represented in the diagram by gray boundaries and Bold italic class labels. Members are represented by small circles with plain font labels. A class contains the members contained in its boundary. A class is a subclass of any other class whose boundary encloses all of its members (e.g., Greek is a subclass of Man).
The reason that members are represented by circles rather than points is that, in some circumstances, members may themselves be treated as classes and extended with additional attributes to form still finer-grained classes (e.g., Socrates the Philosopher, Leonidas the King), which themselves may have one or more members.
It is important to note that a member does not generally "belong to" just one class. In this example, Pericles is a member of the classes Athenian, Leader, Greek, Man, and Being. A
superclass of a class or instance is called a direct superclass if it does not contain any of its other superclasses (e.g., Greek is a direct superclass of Athenian and Spartan, but Man is not).
For example, as illustrated in figure 20, a simple class system, extended with Mortal is shown.
Now we extend the example by adding a representation of the assertion "Every Man is Mortal."
This applies to Socrates, Leonidas, Alexander the Great, et al. It is more compact and convenient than the separate assertions "Socrates is Mortal.", "Leonidas is Mortal.", "Alexander the Great is Mortal."... But more importantly, it generalizes and scales¨an arbitrary number of instances of Man could be added to this class system without also explicitly adding declarations that they have the attribute Mortal with value true. Class systems can lead to efficient structures for storing the attributes of a set of members, even when the number of attributes and the number of members are both very large.
The class Mortal, whose only attribute, Mortal, has the value true in all its members, represented by the dashed line in the diagram, defines a superclass of Man. In this class system, Mortal happens to have the same members as Man, but in general "Every Man is Mortal."
merely indicates that members of the class Man have the attribute Mortal (Man is a subclass of Mortal). A slightly richer class system might include Mammal, Animal, Tree, and other subclasses of Mortal that are not subclasses of Man. (Note also that this example is atypically simple: It is seldom possible to explicitly show very many attributes within this style of class system diagram.) A class system can be used to speed up searches for members of selected classes by first pruning candidate classes. For example, if the desired classes were Mortal and Greek, then the class Mortal could be searched for a subclass Greek, which could be returned without enumerating and checking the members of either Mortal or Greek individually. Similarly, a search for objects that are not-Mortal, could reject the whole class Man without enumerating and checking the attributes of any members.
Because classification and subclassing are deliberately "lossy," classes can also be used to efficiently search for instances that are similar, though not identical.
Members of a class are similar to the degree that they share a set of attributes and attribute values, although they may vary widely in other attributes. In our example, we might expect Plato and Pericles to be more similar than either one is to Leonidas or to Alexander the Great, because Plato and Pericles are both members of Athenian and thus share all the attributes of Athenian (which are not shown in these diagrams). We might also expect all four to be more similar to each other than to Zeus or Atlas, because they are all members of Man.
The practical quality of a given class system may determine the effectiveness of its classes for lossy reasoning, searching, and/or matching. That is, "good" classes in a context may have members that seem similar to users for whom the reasoning, searching, and/or matching are done in that context, because they reflect distinctions that are recognizable and important to those users.
Traditional class system diagrams such as those described above play a role similar to that of Venn diagrams for sets. They can be an effective representation for visualizing a small class system whose representation fits neatly on a single page. Since their interpretation is topological, items and class boundaries may be moved around to shift emphasis and/or to alter their appearance. Subclass relations are easy to see in small class system diagrams.
However, traditional class system diagrams have limitations that severely reduce their usefulness, particularly in large-scale systems, with hundreds to millions of classes, and thousands to trillions of members.
Large diagrams may be infeasible, or prohibitively difficult, to draw, modify, and check, either manually or automatically. (e.g., there was not a lot of room in our simple example to add the class boundary for Mortal, and the members Atlas and Prometheus had to be moved out of the way of the new boundary.) 1. In order to make all the names on a diagram large enough to be readable, the diagram may need to expand to more than fill a screen or piece of paper. The result can be hard to read and understand in its entirety.
2. Classes that cross view frame/page boundaries are particularly hard to envision as single entities.
3. Most large class systems simply cannot be laid out in two Dimensions so that each class is contiguous. (Just as it is typically the case that most graphs are not planar, i.e., capable of being drawn in two Dimensions with no crossing edges).
4. It is almost always excessively awkward to show multiple attributes and their values in this type of diagram.
An alternative way of describing a class system avoids these problems. A
language of class expressions can be used, giving information relating members to classes, relating classes to other classes, or relating attributes to classes. For example, the following set of expressions (-- the precise syntax is not important here, and there are many, many formal languages that can precisely express such information, as exemplified by the number of different Object Oriented Programming (00P) languages --) describes the same class system as the example diagram shown in Figure 20.
Alexander the Great is a member of Man.
Alexander the Great is a member of Leader.
Athenian is a subclass of Greek.
Atlas is a member of Being.
Greek is a subclass of Man.

Leader is a subclass of Man.
Leonidas is a member of Leader.
Leonidas is a member of Spartan.
Man is a subclass of Being.
Man is a subclass of Mortal.
Pericles is a member of Athenian.
Pericles is a member of Leader.
Plato is a member of Athenian.
Prometheus is a member of Being.
Socrates is a member of Athenian.
Spartan is a subclass of Greek.
Zeus is a member of Being.
This defines a mathematically precise class system, although in this example the degree of correspondence to "the real world" (or to any particular user's model of the world) may depend on the interpretation associated with the terms used (e.g., Man and Plato).
Note that the order of the class expressions is as irrelevant to such a description of a class system as the geometry of a class system diagram is to its description. This set of class expressions can be written in any order and still describe the same class system, but some orders may be easier to read and understand than others, just as some diagrams may be easier to view and understand than others.

Long lists of declarations can be made more navigable and readable by adopting simple conventions, for example:
1. Group the expressions related to a class into a contiguous sequence, e.g., class Man subclass of Being, Mortal members Alexander the Great, Leonidas, Pericles, Plato, Socrates 2. Modularize: Organize a long list of class expressions into named modules¨each containing expressions related to a set of related classes¨that may be written and understood fairly independently of other modules, then combine modules as appropriate.
3. Sort declarations in a consistent order, subclasses before superclasses or else superclasses before subclasses, so the reader knows in which direction to search the list for a named class.
These examples illustrate three kinds of errors that often interfere with class-based reasoning, and are especially likely to arise when class specifications from different sources are used together.
1. Different people may have different implicit understandings of class boundaries. For example, many people would probably classify Alexander the Great as a Greek¨even though neither Alexander the Great nor his Greek contemporaries would have had difficulty distinguishing between a Greek and a Macedonian. The class system with Alexander the Great as a member of Greek is also precise, but reasoning based on it could lead to precise, but different, results.

2. Different people may have entirely different definitions in mind for some of the names (tokens, symbols) used¨even for familiar words. For example, one person might associate Greek with the sense "a native or inhabitant of Greece," while another might associate it with "a member of a Greek-letter fraternity or sorority," and a third, with "not understandable" (as in "It's all Greek to me.").
3. A term might have unnoticed overlapping meanings. It is not clear in this example whether Man is intended in the sense "all humans" or "all male humans," since all the given members are male. Such an omission might go undetected until someone attempted to add a class Woman, and had to decide whether or not it was a subclass of Man.
a. If they decide to make Woman a subclass of Man, should they also add a subclass Male Man containing all the previous members of Man?
b. If they decide not to make Woman a subclass of Man, should they also make Mortal a superclass of Woman? And should they add a class, say Human, that is a superclass of both Man and Woman?
c. If they decide to make Gender a new attribute of Man, would the subclass of Man with Gender = Female be more confusing than enlightening?
A considerable amount of standardization of terminology and/or the like is important to reliable interoperation of separately developed class systems and/or class system components. In some embodiments, PERCos systems can provide substantial assistance in avoiding, detecting, and/or correcting such errors.
Embodiments of PERCos may use one or more class systems to help model the flexibility inherent both in human thinking and in natural languages, and/or to improve the clarity of processes and/or results, and/or the efficiency of operations. Class systems may also be used to describe certain aspects of PERCos itself, but the primary focus is on their use to specify and/or manipulate purposes and/or resources. This disclosure primarily discusses two kinds of class systems: user class systems and Edge class systems. These may be distinguished in part by the differing ways in which they are normally used:

1. User class systems include classes used by a human within his/her own mind.
They are generally inherently informal and imprecise, and they are often impressionistic, because that is the nature of human relational thought, organization, and reasoning.
Their subclass and superclass relations are generally correspondingly informal and imprecise.
2. Edge class systems are used for communication¨among users, to the same user in the future (e.g., as aides-memoire), or across the Edge between one or more users and a PERCos system. They contain, but are not limited to, declared classes.
Declarations indicate precise relations among tokens (symbols, signs) that name declared classes and attributes, and are generally intended to approximately mirror relevant portions of user class systems. They can incorporate a variety of user-appropriate tokens.
a. System declared classes are provided by PERCos to provide a basis for interoperation and consistent extension. They are typically created by linguistic and/or acknowledged Domain experts.
b. Shared declared classes have been standardized and published for mutual understanding within one or more communities of users, other stakeholders, and/or one or more PERCos systems and/or subsystems.
c. Personal declared classes may include declarations from a user, and remain local for use by that user, unless and until they are published as Shared declared classes.
Declared class system expressions and their components (e.g., class expressions, attribute expressions, member expressions, and tokens) generally have at least two corresponding representation systems, including one that is human-sensible, e.g., letters, and one that is efficiently machine-manipulatable, e.g., ASCII characters.
These representation systems are normally chosen to make translation among them straightforward.

Note that an Edge class system is precise, yet might fail to correspond exactly to what a user understands¨it may be "precisely wrong" from a particular user's (or group's) point of view, because it corresponds to what has been declared, not to reality or to the user's perception of reality. Such precision may enhance tools that detect and diagnose communication problems.
3. Internal classes are internalized representations for efficient purpose calculation within a PERCos system. They may reference or otherwise be, at least in part, derived from, Edge classes. They may use representation systems that improve the efficiency and/or Outcome of logical reasoning, searching, matching, and/or other internal processing.

User Edge Internal class systems class systems class systems Primary Use Thinking Communicating Machine processing Understood users users and PERCos PERCos and used by tokens and/or Ref/Senses user and user group Vocabulary (standardized for Internal References oriented interoperation and interpretation) Eliminated during Ambiguity Common None Internalization Precise, after tokens Precision user-dependent are disambiguated to Precise Ref/Senses Completeness of Human- and System reasoner-Human-limited Reasoning tool-limited limited Table 1, Comparison of Kinds of class systems Mathematically speaking, in some embodiments, a set of Edge class system expressions might define a theory, and an internal class system normally provides a model of a corresponding theory. In some embodiments, as a set of Edge class expressions grows and evolves, one of the tasks of Coherence processes is to check the set for consistency (to ensure the existence of a valid model), and if it finds inconsistencies, to bring them into consistency, possibly with the interactive assistance of one or more users.
User classes comprise user-identified relational composites that collectively, symbolically, and often impressionistically surface certain underlying human conceptions regarding purposes and resources. They comprise members, items that the user thinks of as "belonging together" in some context. These concepts, and the relations among them, are practical conveniences of thought within a human's mind. They may or may not correspond closely to any external (e.g., written or spoken) form, or to the user classes of any other human¨or even to those of the same human in a different context. As relationally perceived concepts, they may have a variety of primary and more subtle secondary perceptual and psycho-physiological Dimensions.
Something akin to user classes is involved in most purposeful thought, and many user classes may be closely associated with linguistic constructs such as nouns and verbs.
By their nature, user classes do not have precise boundaries. This imprecision is a consequence of the nature of human consciousness, which is mostly an imprecise relational composite, particularly as it perceives and interacts with the "external" world. This imprecision is often useful. Such "looseness" can contribute to flexible and adaptive thought progression. Human dynamic relational perception and thought support and employ both lossy and flexible transformations and abstractions, including use of subclasses and superclasses, to organize wide-ranging and potentially vast collections of items.
A user class may, at least in part, effectively include:
1. Members that share what the user believes to be common attributes (intensive description), for example "tasty food," "hot pie," "warm clothes," "things that weigh less than a pound," "run," "learn plumbing," "fix leak," "travel faster than light," "enjoy sleep," "see movie," "entertain," "educate children."
2. Members that the user selects (extensive description); the Members of the class are determined by the particular instances considered. For example: my "exercises"
are "walk," "jog," "run," and "bike"; my "worrying threats" are "physical assault," "stock market crash," "damage by earthquake," and "destruction by hurricane"; my "favorite flavors of Jell-O" are "Lime," "Cherry," and "Orange"; my "favorite pets are "dogs,"
"cats," and "hamsters."
A user class system comprises a collection of user classes, together with one or more relations, including subclass, which indicates those classes the user considers to be related in some relevant fashion. The imprecision of user classes leads to corresponding imprecision of these relations¨they may generally be impressionistic rather than exact. E.g., a user may think of "Car" as a subclass of "Vehicle" (because "a 'Car' is generally a 'Vehicle"), without considering the precise boundary of either "Car" or "Vehicle," and certainly without enumerating all the members of "Car" and testing them for membership in "Vehicle."
This section discusses various aspects of Edge classes, suggesting ways they may be applied in PERCos embodiments. It uses examples that apply to some embodiments employing certain structures for Edge classes and related concepts. These examples are intended to clarify concepts, without limiting them, and not all examples are meant for express use in other portions of this disclosure. Some PERCos embodiments may incorporate these structures fairly directly, while others may use other concepts, other terms, and/or other definitions in functionally comparable arrangements to achieve functionally similar behavior and results.
Throughout this section, class and attribute denote Edge class (including declared class) and Edge attribute, respectively, unless otherwise qualified.
PERCos Edge classes are precise representations (e.g., specifications), normally intended to reflect human concepts as practical framing for communication across the human-computer Edge. Edge classes that are, for example, to be persisted, reused, and/or published may be declared, giving a short class name (often a single token) for what would otherwise generally be a longer Edge class expression. Such declared classes are generally intended to correspond to user classes and support user processes, as practical method of:
1. communication among humans, 2. communication across the human-computer Edge, 3. classification of items (incorporating, e.g., taxonomies and/or ontologies), 4. articulation and/or specification of conceptual units, 5. identification, interpretation, interaction, and/or purposeful expression of related items and/or concepts, and/or 6. navigation and exploration of information Domains.
Each declared class contains members that have been directly or indirectly declared as similar in certain Contexts. Users may use declared class and attribute names for communication¨to themselves, to other humans, and/or to computer systems¨by methods of expressions composed of tokens. Despite the desirability of aligning user classes and Edge classes, they normally cannot be in exact correspondence, due to the general imprecision of human thought and to aspects of human thought that that are not captured by class systems.
For example, the "closest" Edge class may lack some attributes of the user class and/or possess further attributes.
Such lossiness and/or supplementation in the transformation from user classes to Edge classes may be intended and useful¨for example, to suppress some of the fuzziness of human thought and/or details and natural language nuances and connotations that are not material to the description of the current user purpose.
Classes are generalizing objects used to facilitate communication and computational processes for purpose satisfaction. They may express, in an efficient and practical manner, concept specifications that correspond sufficiently closely to human concepts (particularly user classes) and their organization. They are employed to enable efficient two-way communication across human-computer Edge(s), and in multi-user, multi-Edge scenarios. These generalizing objects enable users to be flexibly exposed to purpose-related information and experiences. Classes further provide practical method of efficiently obtaining purpose-related results from nearly-boundless and disparate resources.

Some key aspects for Edge classes are:
1. Help users and user groups organize thoughts, identify relationships, and/or manage their own knowledge structures.
2. Enhance user concept clarity, relevance, and/or correspondence between user classes and declared classes.
3. Standardize communication among users, user groups, and/or other stakeholders (e.g., publishers).
4. Enhance purposeful user-computer cross-Edge communication.
5. Assist users in cross-Edge processes for navigating, exploring, and developing user classes¨particularly when working with very large information sets, including available knowledge structures (e.g., "Big Resource").
6. Exploit suitably lossy transformations to focus on key characteristics.
7. Provide for user-and-purpose-oriented lossy management and efficient filtering of large, diverse information sets.
8. Provide a method of associating purpose with computer processes and devices.
9. Provide a uniform basis for translation to internal classes to create interoperable knowledge structures.
Declared classes may be created to represent¨at least in part¨related user classes and are generally intended to correspond meaningfully to them. Declared classes normally reflect human concepts as practical framing for communication across the Edge. Many user classes cannot be¨or at least may not be¨fully and explicitly specified.
Naming classes and using them informally are important (explicit and/or implicit) elements of how humans relationally think about and describe purposes and resources.
PERCos supports and reinforces such descriptions by enabling representations of Edge classes (including declared classes) to be communicated across the human-computer Edge using expressions containing tokens, for example, in expressed purposes, in resource attribute requirements, and/or in supplementary contextual information, including user preferences recorded as Participant/Role information.

The inherent imprecision of human thought normally makes correspondences between tokens and human concepts approximate, rather than exact. Correspondences between user classes and declared classes and between user attributes and declared class attributes are normally similarly approximate. If users create Edge class expressions containing declared class or attribute names they don't fully understand, this may lead to confusion about classes they specify.
A declared class meaningfully corresponds to a user class (in a context) to the extent that its specification sufficiently captures aspects of the user class relevant to the user purpose. The degree of meaningful correspondence between an Edge class and a user class is a measure of the degree to which its members and attributes correspond with the user-recognized members and attributes of the user class, i.e., the extent to which the user considers that the members and attributes of the Edge class correspond sufficiently with members and attributes of the user class in that context. PERCos enables isolating the issue of meaningful correspondence to Internalization and Externalization. Other parts of a PERCos system may then deal with precise Edge and/or internal classes, attributes, members, and class systems.
Although, for any particular user class (e.g., purpose element), there is unlikely to be an exactly corresponding Edge class, there should be a relatively small set of standardized Edge classes that correspond closely enough to be useful. For example, "Learn" might correspond closely to a declared class Learn that had subclasses such as Attend Lecture, Do Homework, and Learn Physics, but might not have subclasses precisely corresponding to "Cogitate"
and "Cram."
"Ball" might correspond closely to an undeclared Edge class that is a subclass of classes Spheroidal and Toy. "Play Ball" might correspond to a declared or undeclared subclass of a declared class Play.
To represent a user class, a user should generally choose one or more declared classes that appear to correspond most closely. Names of declared classes may be chosen from available user/group/PERCos lexicons, published extensions, and/or personal extensions.
The tokens used in lexicons for particular Domains may closely correspond to terms that acknowledged Domain experts have distilled out of their own user classes. Normally, the use of standardized declared classes may be important to the interoperability among PERCos subsystems and communication among users.
A user might choose a declared class that does not correspond sufficiently to a desired user class, due to insufficient user knowledge or user error. A user-chosen declared class might thus be more general, less general, and/or otherwise misaligned with the intended user class. But even an unsatisfactory declared class has a precise interpretation as a set of members and can be mapped to a PERCos internal class.
Generally, only the user (if anyone/anything) can sufficiently understand the user's state, including the user's belief in the degree of correspondence between a user class and a declared class. User state may be reflected in user behavior, and hence partially inferred from historical information about uses of declared classes and/or biometric/environmental input. A PERCos system may assist a user by suggesting declared classes (or other Edge classes) that appear to be relevant to an inferred user state, including, for example, candidate Facets, subclasses, superclasses, paraclasses, and/or otherwise related Edge classes.
PERCos embodiments may augment the three traditional kinds of class expression (by attributes, by enumeration of members, and by name) with, for example, and without limitation, additional methods of associating pertinent context with a class expression, including specification of purpose and/or specification of user preferences. This context may be inspected, matched, and/or otherwise analyzed to affect the interpretation of the class expression. Context expressions can be important in guiding computing processes (e.g., in a session) regarding human relational understanding and meaning associated with CPEs and/or declared classes. The use of contextual elements in class correspondence, comparison, and/or matching provides PERCos systems additional efficiency and quality of results over the traditional class.
Contextual analysis may be used in both creating and comparing Edge class expressions, such as CPEs. In some embodiments, PERCos embodiments employ algorithmically combined class-based lossiness through the use of contextual highlights and generalization as a method of effectively dealing with practically boundless distributed information.

PERCos systems may also use annotated classes that attach contextual metadata to Edge classes and/or Edge class expressions that may, at least in part, influence their operational processing.
PERCos embodiments uniquely embrace and employ the inherent lossiness of classes and superclasses as a method to practically optimize both the quality of results and the efficiency of obtaining them, by exploiting relations among classes as a method of managing resources that may be large (at times enormous), diverse, and/or multi-locational. The appropriate lossiness of using classes in place of members and/or using superclasses in place of subclasses provides a method of generalizing and relating purposes and resources. These capabilities may provide substantial improvements over existing search, retrieval, and semantic tools in the identification and deployment of optimally purpose-satisfying resources.
PERCos embodiments may exploit class-based lossy transformations to optimize efficiency and relevance to purpose in various ways, for example, and without limitation:
1. They may narrow a field of search in vast resource sets by rejecting whole classes whose attributes do not sufficiently match a purpose expression, without the overhead of looking at the attribute values of individual members¨the focus can instead be on members of classes that do sufficiently match, providing a substantial improvement in efficiency and practicality.
2. They may broaden a field of search to include additional classes that are sufficiently related to a purpose expression. This may be particularly useful when a scarcity of available matches indicates a need for generalization, and may substantially enhance user discovery and navigation processes by expanding and/or re-orienting their perspectives.
3. They may use relations other than subclass to exploit similarities and/or other relevance that cannot be captured by the subclass relation alone. For example, they may use class siblings, superclasses, and/or Paraclasses to suggest variants of a purpose expression for consideration by the user during purpose formulation and/or to automatically expand a search.

4. They may use classes in combination with Contextual characteristics to provide more nuanced algorithmically managed results, including processing done before, during, and/or after a searching and/or matching sequence.
5. They may exploit the lossiness of multiple classes, for example, representing multiple Dimensions, in compound lossy transformations. For example, they may use algorithms that combine lossiness from different class types, exploiting the differing lossiness attributes of differing class types to facilitate the management of large resource sets, producing, for example, practical purpose-responsive results.
Various embodiments may employ some or all of these techniques in various combinations and orders. In some embodiments there may be one or more choices of convenience which are outlined herein.
The definitions are presented in a generally "bottom up" order. The utility of some definitions should become clearer when the defined concepts are used in later sections.
Viewed mathematically, in a given context:
1. a class system contains a set of classes, 2. each class contains a set of members 3. each member contains a set of <attribute name, attribute value> pairs.
Some attribute values may themselves be classes. A reader might envision classes swimming in a boundless sea of sets.
Some embodiments use sets extensively in the description of classes, because Set Theory is one of the simplest and most fundamental tools of mathematics, and can be used to give a sound and coherent description of important aspects of classes. Similarly, differing embodiments may represent sets in differing ways, in either explicit or implicit forms. In some embodiments, some of the sets may not have any explicit representation within the system.
Most of the examples in this disclosure use English words, phrases, and grammatical categories to explain concepts and uses relating to Edge classes. This is because these are familiar to the authors, and not because there is anything about PERCos or Edge classes that is specific to English (or to any other natural language or collection of natural languages).
PERCos itself is language-neutral, but familiar embodiments are likely to convey more insight than unfamiliar ones. The embodiments described herein are only examples to explain to one of ordinary skill in the art, and not limiting. Any of Arabic, Chinese, Esperanto, Greek, Tralfamadorian, or some artificial invented language could no doubt supply embodiments that would be just as helpful¨
to those fluent in that language.
In some embodiments, users may communicate with the system using primarily words and phrases of a natural language, but, even in those embodiments, there need be no requirement that they use only complete, grammatical sentences. Language fragments focusing on salient aspects of their purposes may generally be the norm, e.g., "learn calculus beginner book", rather than "/
want to learn calculus at a beginning level from a textbook."; "attend concert dead", rather than "/ want to attend a nearby forthcoming concert by the Grateful Dead.";
"learn grow ebeans home", rather than "/ want to learn to grow jellybeans at home."
When the disclosure uses words or phrases as tokens, the disclosure may generally use this font to indicate that they are to be interpreted as tokens, and sometimes use "quotation marks" to delimit single tokens, e.g., these, tokens, "white space", and "for example, and without limitation," constitute four tokens.
The specification/description of elements of classes and class systems may be expressed in one or more suitable languages and/or notations, possibly including interactive elements (e.g., drop-down menus, fill-in forms) that may constrain structure. The syntax of these languages generally can take a number of forms. Each particular embodiment may support a particular selected set of such languages, notations, and/or other communication methods, which may or may not be extensible within the embodiment, and may or may not resemble those used in this document.
A token is a unit for communication across an Edge (a communicable symbol).
Some tokens may be used as declared names¨of attributes (i.e., attribute names), weighted or otherwise algorithmically defined sets of attributes, classes, class systems, structural elements of expressions (e.g., operands, operators, punctuation marks), and the like. A
Vocabulary is a set of tokens.
Although informal speech and writing frequently do not clearly distinguish between a representation of a thing and the thing itself, it is important to be careful about this distinction when talking about classes¨especially declared classes, including purposes¨and to distinguish between a class expression and the class that it represents in a given context.
Tokens may be used, in one or more contexts, to represent PERCos values. For example, the Arabic numeral 14, the Roman numeral X/V, and the binary numeral 1110 may each be used, in appropriate contexts, to represent the number fourteen, which exists as an abstract concept independent of any particular representation. As another example, the operator "+", may in some contexts represent the arithmetic operation of addition, and in some other contexts, the Boolean operation of inclusive or, and in yet other contexts, the string pattern operator one or more.
PERCos expressions are arrangements of PERCos tokens according to the rules of specific description languages. They may be used to represent context-dependent or context-independent values. For example, X/V + // and 4 x4 might each, in certain contexts, represent the number sixteen. The internal representation of an expression is itself a type of PERCos value that could be declared (named). In some embodiments, an expression may also have associated metadata that is distinct from the metadata of the values it may denote. For example, the date and time when an expression was last modified is neither part of the expression, nor metadata about any of the particular values it represents in various contexts.
Communications across a human-computer Edge largely comprise expressions, but "computational meaning" within PERCos largely involves the things the expressions represent, which are internal values (e.g., interpretations of expressions in relevant Contexts). The issue of translating between expressions and values and back (internalization and externalization) is treated in more detail.

An interpretation is a mapping from values (generally expressions) to values;
it may be context-dependent. In some embodiments, the interpretation of at least some structured expressions may proceed by Interpreting each token, including tokens used as declared names, operators, and/or operands, and then operating on those values (which may involve further interpretations) to compute a result.
A PERCos declared name is a (generally relatively short) expression that has been declared, in a context or set of contexts, to be associated with another expression. For example, a single token may be the declared name of a class or an attribute; this allows the token to be used in an expression in place of a literal copy its associated class or attribute expression. Some other examples include structured declared names, which may simplify references to elements of structured values (e.g., A[7].first), and declared names used to defer interpretation (possibly in a differing context, perhaps producing a differing value).
A declaration associates a declared name (a token or other expression) with a second expression (its specification) in a class definition language. The interpretation of the declared name is the same as the interpretation of the second expression. The type of the declared name (and the declaration) is the same as the type of the specification. For example, class declared names are associated with class expressions in class declarations, and attribute declared names with attribute expressions in attribute declarations.
In some embodiments, for convenience of reference, class expressions may have one or more corresponding names. Such names make it convenient to specify a class without enumerating its members or attributes; these concise specifications greatly assist in writing short, yet understandable, CPEs and their class expressions, and greatly assist practical human pattern recognition. A class name provides a concise representation of a set of class expressions in a context: those that the name has been associated with in that context by declaration. Names should normally be chosen to be unique and distinguishable in their context(s) of use, so the set normally has one member. In some embodiments, one or more user-chosen names for a class may be part of a class expression and/or one or more class names may be automatically generated for each class expression.

In many contexts, it is desirable for declared names to be distinct, i.e., each declared name (token or other expression) may be associated with at most one specification, and can therefore be unambiguously Interpreted. In some embodiments, a specification (expression) may have multiple declared names in a single context.
The choice of class and attribute names may affect the perceived correspondence between a declared class and a user class¨due to differences in understanding of one or more of the tokens between the human or human group providing the class expression and humans assuming a user class correspondence. For example, a misunderstanding may be due to a difference in context that changes the understanding of the name. For example, "Everybody knows what point denotes." But is the context Games, Geography, Geometry, Jokes, Pencils, Railroads, or Rhetoric?
Declared classes and attributes are often highly useful in practice, in spite of their inability to correspond perfectly to user classes and attributes. For example, the precision of declared classes may help users understand when they have been using names differently.
They may also provide generalizations and simplifications that improve practicality and efficiency in the computational Context.
A ref/sense is a set of tokens intended to be equivalent representations of a single conceptual unit. In some embodiments, Ref/Senses may be represented by Internal References.
Some simple examples of sets of tokens in string form that might be members of ref/senses include:
1 . . . _ _ _ . . . . . . _ _ _ . . . . . . _ _ _ . . ., SOS SOS SOS, MAYDAY

{ x, *, ., times}
1 acquire, buy, purchase 1 { advanced, expert}
1 American, Yankee 1 { beginner, newbie, novice }
{ bright, brite, shiny }
{ bring, carry, haul, transport }
{ British, Brit }
{ calculus, differential and integral calculus }
{ calculus, pebble, tartar]
{ calculus, predicate calculus }
A purpose class is a class comprising purposes.
An atomic attribute is an <attribute name, attribute value> pair.
An attribute bundle (item) is a set of atomic attributes. Class members are attribute bundles that have been explicitly or implicitly specified as belonging to a class.
Class attribute names are class expressions.
An attribute value is any value allowed by a PERCos embodiment. Some embodiments may allow classes as stored values of Fields.
A method is a kind of attribute value that comprises one or more operations to access some or all of an attribute bundle's other attribute values, to produce one or more values derivable at least in part from those attribute values and/or to achieve one or more particular effects on attribute values of the bundle (i.e., to generate a new attribute bundle modified in a particular way).
Methods may be specified by, for example, one or more programs, functions, sets of rules, logical expressions, and/or other descriptions of the characteristics of those values and/or effects. Normally, methods are "invoked" as an aspect of the unfolding of a PERCos process.
Fields are attributes that are not methods. In some embodiments, each field may have associated access methods (assignment and retrieval), conventionally called put and get.
A Predicate is a Field whose attribute value is restricted to be true or false.

Simple examples of attributes might have names such as height, weight, price, and currency, and values that are numbers (for height, weight, and price) or elements of a pre-established set, such as { Dollar, Pound, Euro, Yen, ...} (for currency).
An attribute's Range in an attribute Bundle is the set of attribute values paired with the attribute's name in any of its Atomic attributes. For example, in the attribute Bundle { <weight, 17>, <price, 345>, <weight 19> }
the Range of weight is { 17, 19 } and the Range of price is { 345 }.
An attribute name is Single-valued in an attribute Bundle if it occurs in a single Atomic attribute, and Multi-valued otherwise. In the example above, price is Single-valued and weight is Multi-valued.
An attribute bundle is Single-valued if each of its attribute names is single-valued and Multi-valued otherwise; i.e., if no attribute name is paired with more than one attribute value, the attribute bundle is single-valued.
If attribute name a is single-valued in the attribute bundle B, let v be the attribute value paired with the name a by an atomic attribute in B. In this disclosure, we sometimes use the notation B.a to represent either 1) if v is a Field, the result of invoking v's get method, 2) otherwise, v.
B.a may be viewed as a "state variable" of B, and may sometimes be called "attribute a of B." If a is a (potentially Multi-valued) attribute name in B, we sometimes use the notation, B.. a, to represent the set of attribute values paired with attribute name a in the atomic attributes that comprise B.
A class is a set of attribute bundles, which are called its members.
The attribute name set (often shortened to "the attributes") of a class is the set of attribute names that appear in every one of its members.

The range of an attribute in a class is the set of attribute values that are paired with the attribute name in any atomic attribute of any class member. Equivalently, it is the union of the Ranges of that attribute in all the members of the class.
An attribute-defined class is a class comprising the attribute bundles that pair a specified attribute name (the defining attribute) with true.
A Fixed attribute of a class is one that has the same attribute value for all members. For example, it might be a field named x and have the value 7, or it might be a method named clear, which, when invoked, has the effect of set-ing the value of each of a member's Fields to the value 0. Fixed Fields may omit the put method (or it may be a method with no effect). Methods themselves are commonly Fixed, but in some embodiments, some or all of them may be assigned dynamically.
Class A is a subclass of a class B (written A c B) and B is a superclass of A
(written B D A), if every member of A is a member of B.
As discussed in previously, the subclass and superclass relations between classes can be tools for controllably managing and exploiting lossiness in PERCos.
Inheritance signifies that each subclass includes (inherits) all the attributes of each of its superclasses (i.e., the attribute name set of a class is a subset of that of any of its subclasses).
Further, the Range of each attribute name in a class is a superset of its Range in any subclass.
These two properties follow directly from the definition of subclass and superclass.
Inheritance is an important property of the subclass relation. It leads to much of the conciseness and power of Object-Oriented Programming, and provides similar aspects in the description of purposes, resources (e.g., Participants, devices, applications), and some elements of PERCos embodiments by class expressions.
The subclass and superclass relations are transitive (A c B and B c C imply A
c C), which follows directly from their definitions.

The subclass and superclass relations define dual mathematical lattices over the space of classes, a property that may be useful in pruning searches at the class level, without examining individual members. Furthermore, as discussed later, classes can provide additional information about attributes and/or members that may be useful in describing and/or embodying PERCos.
In some embodiments, a member of a class may be modified by a PERCos process and/or by invocation of a method that assigns one or more attribute values to one or more of its attribute names. Assignment may generally operate on a member (of one or more classes), rather than on any of its containing classes. The result may remain a member of the classes for which it satisfies all symbolic, Range, and/or class Restrictions. Invoking the set method of a Field is a standard form for assignment to the member.
A replacement assignment is one that deletes from the member all atomic attributes with the same attribute name as the one being assigned before adding the new atomic attribute.
An additive assignment adds a new atomic attribute into the attribute bundle without removing any atomic attributes. Additive assignment is not generally applied to members of classes specified to be single-valued.
For example, suppose that class expression 2DIntCoord has attributes named x and y.
1<x, 3>, <y, 1>1 might be a member of 2DIntCoord's class. It could be modified by replacement assignment of the value 7 to y, producing the attribute bundle 1<x, 3>, <y, 7>1 or by additive assignment of the value 7 to y, producing 1<x, 3>, <y, 1>, <y, 7>1. The former would be a member of 2DIntCoord's class if y were purely abstract in that class. The latter could not be a member if 2DIntCoord and/or its attribute y were declared to be Single-valued.

To this point, the disclosure has treated classes as ordinary mathematical sets: at any given time, in any given Context, an item is either a member of a class or it is not¨there is no middle ground. There has been considerable research on Fuzzy Sets, developing mathematical models that reflect, in part, uncertain and/or imprecise human classification boundaries, such as those involved in user classes. Fuzzy sets address some, but not all, of the problems by defining the result of testing membership in a Fuzzy set as a probability p, rather than a Boolean.
Some embodiments of PERCos may use Fuzzy sets, rather than ordinary sets, as the basis of some or all classes. Relations, including the subclass relation may also be generalized, for example, so that one class is a Fuzzy subclass of another with a probability p, rather than with a Boolean value. Using appropriate operators from Fuzzy sets as appropriate, classes can be generalized to have the properties discussed above, and be Fuzzy, too.
There are several reasons the disclosure has not discussed this generalization earlier:
1. It is difficult to give comparable definitions of class-related concepts without resorting to substantially more mathematical notation.
2. Some mathematical operations and logical reasoning using Fuzzy classifications can lead to results that humans find surprising and/or unreasonable, which may, in many circumstances, be undesirable in a system with the aspects of PERCos.
3. Within a computer system, operations based on Fuzzy classes, including searching and evaluation, may be less efficient than corresponding operations based on set-based classes.
4. Users may find it difficult and/or problematic to consistently specify their degree of uncertainty about the membership probabilities of some Fuzzy members of Fuzzy classes.
5. Different users are likely to assign somewhat different probabilities near boundaries between Fuzzy classes (e.g., because their personal user classes are slightly different), but each Fuzzy class system reflects just one of them.

6. In human thought, context may radically change the boundaries defined by many attributes and/or classes: Think of a "big mouse" and a "small elephant." As generally defined, Fuzzy Sets are context-independent.
7. The degree of membership in a Fuzzy class may be dependent on contextual parameters that are unidentified or unclear to users.
The use of threshold class expressions may in many instances provide a sounder and more practical approach to the problems Fuzzy Sets/Logics/classes were intended to solve, although in certain circumstances the use of Fuzzy classes may improve results.
A class expression is an expression that specifies a class (set of members)¨or an element of such a specification¨expressed in some class Description Language, which may include interactive elements (e.g., drop-down menus, fill-in forms) that may constrain class expression structure.
In some embodiments, a class expression may have associated metadata, distinct from the metadata of the class or its members.
An interpretation provides a possibly context-dependent mapping from values (including class expressions) to values (including classes, attributes, members, and expressions).
Purpose expressions are a subset of class expressions, and purpose expression elements are operative elements of Edge class expressions.
A class expression may have one or more associated class names, which may be single tokens or other class expressions. A class name may be used in expressions to represent the class that is the interpretation of its associated class expression. The disclosure may often shorten "the interpretation of the class expression associated with the class name X" to "class X."
Class expressions may be expressed in one or more class expression languages accepted by an embodiment. In some embodiments, class expression languages provide constructs for declaring various kinds of information about a class. For example, and without limitation, a class expression may indicate that:
1. A class is a subclass of one or more other classes.
2. A class has one or more named attributes, which may be Fixed, Abstract, and/or symbolic.
3. One or more specified attributes of a class are Single-valued in all its members.
4. The attribute Range of a specified attribute of a class is included in a specified set of attribute values and/or included in one or more specified classes;
The foregoing types of class expressions may be used in any appropriate combinations to form specific descriptions of classes. These forms of class expression are similar to forms that have been used in various Object-Oriented Programming languages and/or ontology description languages, and constitute the Traditional Forms of class expressions.
In some class expression languages, a subclass expression declares that a class is a subclass of one or more specified classes.
In some class expression languages, a Fixed attribute expression declares one or more attributes of a class to be Fixed, with the interpretation that the attributes may be contained in the class's attribute name set, and each attribute name may have the same specified attribute value (or set of attribute values) in each member.
In some class expression languages, an Abstract attribute expression declares one or more attributes of a class to be Abstract, with the interpretation that the attributes may be contained in the class's attribute name set. This implies that each class member may have attributes with those names, but does not restrict their attribute values.
In some class expression languages, a symbolic attribute expression may declare one or more abstract attributes of a class to be symbolic, represented by one or more given symbolic expressions that may contain the symbolic attributes, other attributes and/or contextually relevant Dimension values. The interpretation of a symbolic attribute expression is that, in any context, each class member may have attributes with those names, whose values¨together with the values of the other attributes and the Dimension values¨satisfy the symbolic expression.
For example, a symbolic field named r might be expressed as the square root of the sum of the squares of the attribute values of the Fields named x and y in that same member. Or the method named Mean might be specified as returning the result of dividing the value returned by the method named Sum by the result returned by the method named Count, of the containing member.
Some class expression languages may restrict symbolic expressions to equations with attribute names as their left hand sides, for example:
r = sqrt(x2 + y2) Some other class expression languages may allow more general symbolic expressions, including predicates that are not equations and/or equations with more complex expressions on the left hand side, for example:
a3 + b3 = c3 + d3 where a and d name symbolic attributes, and b and c name Fixed attributes.
In some class expression languages, a restriction expression may declare an attribute to be restricted, with the interpretation that the range of the attribute name in the class may be included in a specified range and/or in one or more specified classes, which may be context-dependent.
The operational range of a class expression in a PERCos system is the set of classes that may be its interpretation in any context that is possible during operation.
In some embodiments, class expressions, classes, and/or members are normally packaged as resources.

A single class may be the interpretation of multiple differing class expressions. In a given context, differing class expressions can have the same result (set of members) when Interpreted, even though they may, for example, group elements differently, present them in different orders, or involve differing class and attribute names.
Unlike many non-PERCos class systems, the interpretation of some PERCos class expressions may be interpreted as differing classes in differing contexts. For example, a symbolic class expression may refer to contextual values. In some embodiments, these symbolic expressions may be explicitly conditional, for example magnitude = if Context. CoordinateSystem = Cartesian then sqrt(x2 + y2) else abs(r) where x and y are Cartesian coordinates, and r is the radius in polar coordinates.
Class expression AD is said to be a subclass expression of class expression BD
under interpretation / in context C if AD's interpretation (a class) is a subclass of BD's interpretation.
Thus the subclass relation for class expressions may be dependent on interpretation and/or context. It is context-invariant under / if for every context, /'s interpretation of AD is a subclass of /'s interpretation of BD. For example, this may be the case if AD contains an expression declaring BD as a superclass of AD.
Every member may be associated with a unique class that contains only itself.
In some embodiments, in contexts that may require a class expression, a member expression (e.g., a member name) may be automatically converted to its associated class, and then used like any other class.
A class system comprises a set of classes and a set of relations on those classes that includes at least the subclass relation.
A binary relation is a Boolean function (predicate) that is true of a pair of elements if they are "related" for some purpose. Other relations may involve more than two classes.

Subclass and superclass are not the only useful relations between classes, members, and/or attributes. For example, a relation between two classes might hold if the two classes were "semantically and/or purpose close," regardless of whether they shared the same attribute set or had a subclass relationship. Relations may provide additional perspectives, and/or efficiencies for processing. Relations may be used, for example, in assisting a user who is exploring an area to locate relevant purpose classes and/or other classes described using a differing set of classes or class names than the user initially used.
A member introduction is an assertion that certain items are actual members of one or more classes, or that they are actual members of a class system (and all of its classes whose constraints they satisfy). Most embodiments allow new actual members to be introduced dynamically. An item that is consistent with a class's constraints, but has not been introduced as a member is a potential member of that class. (Actual member is normally shortened to member, unless there is likely to be confusion with potential member.) A class system may be specified by a set of class expressions that declare classes and their relations, together with a set of member Introductions. A class system normally also includes all unnamed classes that may be expressed by class system expressions using its declared classes and attributes.
Some class system embodiments may include a class system's Top class (written T) is the superclass of all classes in the class system. Some class system embodiments may include the Empty class, the class with no members, which is a subclass of all classes in the class system and is sometimes called its Bottom class (written 1).
A class system's actual member class comprises the set of all actual members of its classes. In some class system embodiments the actual member class may be the same as the class system's top class.
A class system is static if none of its classes or attributes may be changed by processes, extensible if either or both of them may be added to, and dynamic if either or both may be added to, subtracted from, and/or otherwise modified. For efficiency, some embodiments may restrict some or all of their class systems, or portions thereof, not to be dynamic and/or extensible.
A purpose class system is a class system comprising purpose classes.
In many embodiments, class systems may be resources. Some embodiments may use multiple class systems, which may or may not have classes, attributes, and/or actual members in common.
Adding a single actual member to a class system doubles the number of possible classes in the class system. (This is actual, rather than just figurative, exponential growth.) Thus, in practice, many class systems are so huge that their full set of classes may never be explicitly written, computed, or enumerated, only the much smaller number of classes that are relevant to some process set, such as matching or searching. In addition some class systems contain an infinite number of classes.
An Edge class system expression is an expression that is part of the specification of an Edge class system, expressed in some Edge class system description language, for example, by an arrangement of a token set, by an interactive user interface, and/or by the result of a resource assimilation process. Edge class system description languages normally include one or more class description languages.
Communication to and from users and other stakeholders normally uses Edge class system expressions. Within this section, class system denotes Edge class system, unless otherwise qualified.
A class system expression may supply one or more constraints on a class system and/or one or more of its classes. In some embodiments, a class system expression may, for example and without limitation, use specifications of some or all of the following forms:
1. Declare a class.
a. A class may be declared by associating a class name with a class expression.

2. Specify one or more constraints on a class.
a. A class attribute for a class may be declared by associating an attribute name with an attribute type, a range of attribute values, a symbolic expression involving other attributes and/or Contextual information (a symbolic attribute), an indicator that the attribute is Abstract in the class, and/or an attribute weight.
b. A class's members all meet one or more thresholds on corresponding specific member metrics.
3. Specify a class in terms of one or more other classes, using, for example, class Constructors.
a. It contains the symmetric or asymmetric difference of two or more other classes.
b. It is a Combinatorial joining of a set of base classes¨its members are members of at least k of n specific base classes.
4. Specify a class by other method.
a. Its members are determined by an expression in some logic (e.g., Description Logic, Modal Logic, Temporal Logic, First-order Logic, and/or Higher-order Logic).
b. Its members are determined by a specified algorithmic method.
5. Specify one or more relations (and/or parts thereof) among two or more classes and/or their members.
a. A class is a subclass of one or more other classes.
b. A class has one or more other classes as paraclasses.
c. A class or one or more of its members is related to one or more other classes and/or members by one or more specific relations.

6. Specify a class expression in terms or one or more other class expressions, using, for example, class expression Constructors.
a. It is an Augmentation of a class expression¨it contains one or more additional identified items as members.
b. It is a Relaxation of a class expression¨it overrides inherited restrictions on one or more specific attributes.
c. It is a Widening of a class expression¨it adds members on the basis of one or more specified relations.
7. Specify a constraint among two or more classes and/or their members.
a. A class is equivalent to (i.e., it has the same set of members as) a class specified by a different class or class system expression,.
b. A set of classes pairwise have a bounded number of members in common.
8. Introduce one or more explicit members.
a. An item is a member of the class system and/or of one or more of its classes.
Class system expressions may be built up iteratively and/or recursively using such forms. Many class system expressions may include multiple forms. Various PERCos embodiments may allow various combinations of these forms, possibly with others of a similar character. These forms may enable natural, compact, and/or operationally efficient expressions for many useful classes.
In some embodiments, a class system expression may have associated metadata, distinct from the metadata of the class system or its elements.
An Edge class interpretation function¨in any given context¨maps a set of Edge class system expressions (including member Introductions) into a class system (e.g., an internal class system).
Differing interpretation functions may normally map a given set of expressions to differing class systems. In some embodiments, for efficiency purposes, smaller class systems (i.e., ones with fewer declared classes and/or Actual members) are favored over larger ones. A
combination of an Edge class interpretation Function and a set of Edge class system expressions is generally called an Edge class specification.

There may be multiple Edge class specifications that define the same Edge class system, i.e., there may be multiple ways of Specifying a class system. This reflects the fact that a set of classes and their relations can usefully be described in many different ways.
Such Edge class specifications are structural variants of each other. Different structural variants may result from different perspectives on "the same things" and/or differing sets of declared classes intended to represent differing sets of user classes used for mental organization and/or purpose classes. The sets of classes and/or purpose classes that they declare may differ, and their interpretations may differ, yet they may still specify the same set of classes and class relations.
In some embodiments, a PERCos system may have one or more, possibly context-dependent, base internal class systems and one or more Edge class systems that all map into one of the base internal class systems. A class system may contain some classes that are interpretations of class expressions that use only traditional forms of class expressions and/or some classes that are interpretations of class system expressions that use one or more of the additional PERCos forms, such as those discussed in this section.
The vocabulary of a class system is the set containing each token that appears in any one or more of its class system expressions and/or is allowed in any of the embodiment's class system declaration languages, including those used as class names and attribute names.
In some embodiments, some or all class systems are resources that may be published.
Specifying attributes of a class. Some embodiments may provide additional forms of expressions for specifying constraints on a class. For example, metrics may allow additional forms of class specification, such as threshold classes.
If a weight is associated with an attribute declaration, it may be used to resolve Inheritance conflicts, for example, by Coherence processes. Some embodiments may, in some circumstances, use a simple metric for the weight (e.g., either mandatory or optional) and/or a more detailed, or even continuous, metric (e.g., a number between 0.0 and 1.0). In some embodiments, the value of a weight may be determined in the context of the attribute declaration and/or be an expression to be evaluated in the context in which the conflict is being resolved.

Such expressions may be conditional and/or involve computation at the time of evaluation (in the current context).
In some embodiments, the use of metrics to weight expressions and/or classes, attributes, and/or members represented by expressions, may be used in certain forms of class specification. For example, a threshold class expression specifies that all members have values that pass a specific threshold value of a specific metric, which may be context-dependent.
The value of a metric applied to an item might be determined in accordance with a formula involving classes, attributes, members, and/or other context. For example, a weight might be associated with each of a set of base class expressions; an item's weight could be the sum (or the product, or some other function) of the weights associated with the base classes of which it is a member. If the base weights were all the same, such an additive threshold class expression would be equivalent to a combinatorial class expression.
In some PERCos embodiments, a metric's value may depend on the relative importance and/or frequency or probability of occurrence of an item, and/or its tightness of coupling, importance, similarity, nearness, matching, and/or other measure, relative to one or more given members, classes, and/or contextual elements.
Metrics and/or threshold class expressions may be standardized, at least in part, by acknowledged Domain experts to support interoperation and common understandings.
Differences among classes may also be used to specify classes. The base classes whose differences are taken may be represented by differing class expressions and/or interpretations of a class expression in differing contexts.
Specifying that a class is the asymmetric difference of two or more other classes denotes that members of its interpretation are members of the interpretation of the first that are not members of any of the others.

Specifying that a class expression is the n-symmetric difference of two or more class expressions denotes that members of its interpretation are members of the interpretations of at least one of them, but not more than n of them.
It may be useful to publish class difference expressions to allow other users and/or other stakeholders to include the differences to augment and/or to add tokens, ref/senses, class structures, classes, and or attributes to their locale, or to facilitate the harmonization (through Coherence processes) of differing lexicons and/or expression structures.
In some embodiments, combinatorial class expression simplify the expression of classes that are most easily described informally using words like "or" and "and/or."
For a given k and n, a combinatorial class expression's interpretation is a class whose members are members of the interpretations of at least k out of a set of n base class expressions. For example, a combinatorial class expression might declare that its interpretation's members are members of the interpretations of at least six out of a set of ten base class expressions. This is somewhat analogous to the way medical diagnostic manuals may define a syndrome by saying that patients have the syndrome if they exhibit at least six out of ten listed symptoms.
For example, let k = 2 and n = 4, and the base class expressions be { A, B, C, D }. Then the combinatorial class's interpretation is a class whose members are those that are members of the interpretations of A and B, A and C, A and D, B and C, B and D, and/or C and D. When k and/or n are large, the notational compactness of combinatorial class expressions can supply conciseness, clarity, and efficiency.
When k = 1, a combinatorial class expression is called a union class expression¨its interpretation is a class consisting of all members of the interpretations of any of the base class expressions. Some class expression languages may provide special syntax for this useful case.
An example would be specifying the interpretation of Major Party members to comprise members of the interpretation of at least one out of the two base class expressions, Democratic Party, and Republican Party. Note that this is a more restrictive specification than specifying that Democratic Party and Republican Party are both subclasses of Major Party, which would allow the possibility of there being other members of Major Party.
When k = n, a combinatorial class expression's interpretation is a subclass of each of its base class expressions. However, when k < n, a combinatorial class expression does not necessarily specify a subclass of the interpretation of any of its base class expressions.
PERCos embodiments are not restricted to a fixed set of class description languages. Some embodiments might, for example and without limitation, allow the use of various logics and/or algorithms for the specification and/or enumerations of members of some classes.
Various logical systems (e.g., description logics) may be useful as class system description languages, or portions thereof. There has been considerable recent research in this area that might be leveraged by some embodiments. The goal is to identify forms of expression that enable efficient reasoning at the class (or class expression or class system expression) level, rather than reasoning purely or primarily at the level of individual members.
The difficulties that have been encountered in this area appear to may require that great care be taken in choosing the "expressive level" of the logic: Logics that are adequately expressive often turn out to be computationally inefficient, or even undecidable; logics that are efficiently decidable often turn out to be inadequate to express all that needs to be said about some kinds of commonly-occurring class systems. Nevertheless, it appears that with judicious choices, it may be possible to do useful amounts of checking of realistic logic-based class system expressions, to assist in their development and "debugging" (to improve their conformance to user purpose).
A computed class expression is interpreted as a class whose members are determined, at least in part, algorithmically. In some embodiments, computational tests and/or other algorithmic methods may be used to determine membership and/or to enumerate the members the interpretation of a computed class expression. Context, including historical user and/or user group usage information and/or reference sources, may contribute to the interpretation of a computed class expression.

In some embodiments, restrictions may be specified to ensure that the interpretations of some computed class expressions are subclasses of the interpretations of certain designated base class expressions, as an aid to optimizing searching and matching. Computed class expressions may inherit attributes from these specified superclasses.
As with logic-based class description languages, the price of allowing completely general computed class expressions would be that, in certain circumstances, it might be difficult to reason about, check for consistency, and/or otherwise utilize, Edge class systems involving expressions in such languages, because of undecidability of important properties. If care is exercised in the class of algorithms that are allowed, or sufficient specification of the algorithms may be required, computed class expressions may provide compact specifications of useful elements of class systems that are difficult and/or impractical to specify using only traditional Forms.
Subclass and superclass are very important, but they are not the only relations between classes, members, and/or attributes that may be useful in purpose calculation, navigation, and/or exploration. For example, a relation between two classes might hold if they were "semantically and/or purpose close," regardless of whether they fully shared the same attributes and/or had a subclass relationship. Other relations, representing, for example, "relational correspondence,"
"see also," "relevant supporting knowledge," "comparable" (which might, in some contexts, be a broader or otherwise more useful relation than "equivalent"), or "contributing to comparable"
may be useful in navigation and/or matching. Such relations may provide additional (general and/or Domain-specific) hierarchical and/or non-hierarchical perspectives on, and/or efficiencies for processing, relationships among classes, attributes, and/or members.
A binary relation is a Boolean function (predicate) that is true of a pair of elements if they are "related" for some purpose. Relations may be used, for example, in assisting a user who is exploring an area to locate relevant purpose classes and/or other classes described using a different set of classes or class names than the user initially used. For example, Learn."Do Homework" and Leam."Solve Exercises" or Physics.Molecular and Chemistry.Physical might be specified, in some contexts, to be in the "semantically close" relation.

Relation expressions may be very general, or quite Domain-specific. Other examples, without limitation, include the relations:
1. General:
a. "synonym," which denotes that they are functionally sufficiently comparable, b. "antonym," which might be used, for example, to assist a user to find a counterpoint, contrary, or competing view, c. "complement," which pairs purposes that have inverse roles (e.g., <Teach, Learn>, <Buy, Sell>) and might be helpful in finding purposes described from complementary viewpoints d. "is a part of," which pairs components with their containing entities, e. "has the same structure,"
f. "is provided by,"
g. "is located near,"
h. "may replace,"
i. "contributes to," (e.g., contributes to the creation and/or functioning¨drought contributes to forest fire), j. "related but different" according to a specified metric.
2. Domain-specific:
a. Rows and columns of the Periodic Table of the elements, b. Aspects of subatomic particles, according to the Standard Model, c. Correspondences between minerals and geological strata and/or paleontological eras, d. Useful recipe constituent substitutions, e. Systematic relations among phonemes and phoneme shifts, and f. Compatible fabrics and dyes.
A binary relation may conceptually be viewed as a matrix, where the value true indicates that the row element and the column element are in the relation. For example:

Is Perceptually Close 1. 2. 3. 4. 5. 6. 7. 8.
1. Red X X
X
2. Orange X X X
3. Yellow X X X
4. Green X X X
5. Cyan X X X
6. Blue X X X
7. Blue-Violet X X
X
8. Magenta X X
X
An X at the intersection of a row and a column represents "true" and a blank represents "false."
An X in this matrix says that the color named on the row is "perceptually close" to the color name whose number heads the column. For example, Magenta is "perceptually close to Red, to itself, and to Blue-Violet. This is a representation of the well-known "color wheel."
Is a Part of 1. 2. 3. 4. 5. 6. 7. 8. 9.
10.
1. Asteroid X X
2. Black Hole X
3. Comet X X
4. Galaxy 5. Moon X X X
6. Planet X X X
7. Planetary System X X
8. Ring X X X
9. Solar System X
10. Star X X

This table, for example, indicates that a Moon is "part of' a Planetary System, a Solar System, and a Galaxy. Such a relation is often called a "partonomy" by ontologists.
A class expression may include any number of relations. Relations may generally be defined by acknowledged Domain experts and/or through the analysis of historical patterns of use. In some embodiments, there may be provisions for users and/or groups to specify private relations for their own use, and/or to publish relations for potential use by other users and/or groups. Such relations may be standardized to improve interoperability, efficiency, and/or inter-understandability, especially when traversing the Edge class to internal class boundary. For example, an organization might publish an organization chart.
Many useful relations may be "sparse" (have a tiny minority of true elements), so various well-known sparse matrix representations and/or algorithms may be efficient embodiments. Even some non-"sparse" relations may have efficient algorithmic embodiments. For example, the "color wheel" relation can be represented by the formula I (row ¨ column) modulo 8 I 1 PERCos systems may use differing representations for relations. Some may have as many different representations as they have relations¨or even more, using mixed representations for some particular relations. Others may use only one or a few standard representations for relations.
Relations may, in some embodiments, be defined using one or more relational description languages, which may provide various operators for specifying them.
Some embodiments may support non-binary relations, involving more than a pair of elements, for example between (A, B, C), which represents the notion that, in a certain Context, B is "between" A and C. For example, between (Red, Orange, Yellow), between (small, medium, large), or between (Palo Alto, Menlo Park, Atherton).

The context-dependent paraclass relation is a "relaxed" version of the subclass relation. A class may be a paraclass of another class (or an item may be a member of a paraclass of a class) if, in the current Context, it is determined to be "sufficiently similar" to the members of the class and/or commonly "lumped" by users with other members of the class¨even if it is not actually a subclass (or a member) of the class. For example, Whale, Dolphin, and Porpoise might be paraclasses of Fish, even though they are all biologically Mammal. Tomato and Cucumber might be paraclasses of Vegetable, even though botanists classify both as members of Berry, a subclass of Fruit. Lease and Barter might be paraclasses of Buy; Para-legal might be a paraclass of Lawyer; Para-medic might be a paraclass of Doctor. Paraclasses may be specified in a class system in a variety of ways, for example, without limitation:
1. A class may be explicitly specified as a paraclass of another class.
2. A paraclass may be obtained by Interpreting the class expression of a Facet Division, without applying the restriction that members of the Division may also be members of the Faceted class.
3. A paraclass may be identified by using a given Context-dependent metric to compare the attributes and/or attribute values of members of one class with those of a potential paraparent class to decide whether a sufficient number of its members have characteristics sufficiently similar to the paraparent to qualify as a paraclass.
4. A paraclass may be formed computationally (possibly without a name) using a given metric to statically or dynamically compare the attributes and/or attribute values of items to determine those that are sufficiently similar to a paraparent class to comprise one of its paraclasses.
A paraextension of a class is a (possibly declared) superclass of the class comprising the class and one or more of its paraclasses. For example, a declared class Fishlike, comprising Fish, Whale, Dolphin, and Porpoise, might be a paraextension of Fish.
A parafringe of a class includes members of one or more of its paraclasses that are not members of the class itself. For example, a parafringe of Fish might comprise Whale, Dolphin, and Porpoise and a parafringe of Vegetable might comprise Tomato, Cucumber, or other fruit thought of as a vegetable.

The interpretation of a class expression may be augmented by declaring additional identified items as actual members. This includes the case where the class would otherwise be empty, so a new class expression may be specified by augmenting a class expression whose interpretation is empty by an enumeration of members. In some embodiments, an Augmentation may, in certain circumstances, override subclass and superclass specifications that would contradict it; in other circumstances, the Augmentation may be propagated to superclasses, in still others, the conflicting element of the subclass/superclass relation may be removed.
Augmentations may be temporary (within a given process, time span, and/or other context) or persistent. Some embodiments may restrict or allow temporary and/or persistent augmentation.
A relaxation of a class expression overrides inherited constraints on one or more attributes with weaker constraints, thereby broadening the class expression's interpretation and defining a superclass. This includes the case of no constraint at all, in which case the attribute is effectively specified to be irrelevant in a context. This is sometimes referred to as "ignoring an attribute," or "projecting out an attribute." Relaxation may be useful, for example, in situations where it is possible not to use all available information¨it is a controlled form of intentional lossiness¨for example to make certain processes more general, more efficient, and/or more flexible. Some embodiments may use relaxation in early stages of searching and matching in order to focus on certain other attributes (e.g., Core purpose Facets) and/or attribute Ranges while ignoring, or giving lesser weight to, others.
Relaxation may eliminate or "soften" search and/or matching criteria, for example and without limitation, to:
1. reduce complexity, 2. improve efficiency, and/or 3. introduce greater generality for navigation and/or exploration purposes.
Relaxations may be temporary (within a given process, time span, and/or other context) or persistent. Some embodiments may restrict or allow temporary and/or persistent relaxation.

A widening of a base class expression causes the interpretation to include not only the members of the base class, but also selected related members. For example, and without limitation, items might be declared to be related members if they:
1. are related to some member of the interpretation of the base class by at least a given number of selected relations and/or by other algorithmic combination of relations;
2. are a member of a class related to the interpretation of the base class expression by at least a given number of selected relations and/or by other algorithmic combination of relations;
3. are a member of a class related to some member of the interpretation of the base class expression by at least a given number of selected relations and/or by other algorithmic combination of relations;
4. have attributes related to attributes of the interpretation of the base class expression by at least a given number of selected relations and/or by other algorithmic combination of relations; and/or 5. satisfy one or more conditions, based at least in part on relations and/or Context, for example, through algorithmic methods, events, triggers and/or thresholds.
In some embodiments, a widened class expression may be specified to be interpreted as a subclass of a particular class; other embodiments may not allow such a restriction. Widenings may be temporary (within a given process, time span, and/or other Context) or persistent. Some embodiments may restrict or allow temporary and/or persistent widenings.
Widening may usefully create broader classes, particularly for navigation and exploration, that include members on the basis of one or more relations. This may avoid some of the pitfalls of taxonomies that insist on placing each item at a single place in a hierarchical description and/or ontologies that fail to recognize the "closeness" of some distinct classes, e.g., "Physical Chemistry" and "Chemical Physics," "College Athletics" and "Professional Sports,"
"Manufacture" and "Make," "Study" and "Learn," "Provide" and "Sell." It may also be useful, for example, in broadening searches that fail to return sufficient results, or in assisting a user in navigating and exploring an area in which that user is not expert.

Certain particular widening relations may be indicated by, or closely bound to, certain purpose expressions, and may be selectively or automatically, at least in part, employed in the context of those expressions.
Widening is similarly useful to relaxation for "softening" search and/or matching criteria, improving efficiency, and/or productively generalizing for exploration and/or discovery purposes.
A class expression may be specified to be equivalent to another under a one-to-one name mapping (which may be optional), implying that in any Context, and with any interpretation, the interpretations of the two class expressions (after the systematic mapping of the first's names) contain exactly the same members. There need not be any structural similarities between the class expressions themselves. Since they contain the same members, they may consequently have (after mapping) the same attribute names and superclasses. Such expressions may themselves refer, for example, to classes appearing in other class equivalence expressions.
Equivalence is transitive, so that if A is Equivalent to B, and B is Equivalent to C, it follows that A is Equivalent to C.
A class expression may be specified to be approximately related to another under a one-to-one name mapping (which may be optional), implying that in any Context, and with any interpretation, the interpretations of the two class expressions (after the systematic mapping of the first's names) may contain similar and/or overlapping members. There need not be any structural similarities between the class expressions themselves. Such expressions may themselves refer, for example, to classes appearing in other class equivalence and/or approximation expressions.
Specifying that a set of class expressions has bounded overlap denotes that any set of n (e.g., pair for n = 2) of their interpretations has at most and/or at least a specific number, percentage, particular set, and/or algorithmically determined range of members in common.
An important special case is specifying that they are disjoint, which signifies that no pair of their interpretations has any members in common.

A member introduction is an assertion that certain items are actual members of the interpretations of one or more class expressions, or that they are actual members of a class system and all of its classes whose constraints they satisfy. Most embodiments allow new actual members to be introduced dynamically. Potential members are other items that would satisfy all conditions for membership in one or more of the classes specified by a set of class system expressions, but have not yet been (and perhaps never may be) introduced. Actual members are operatively available, whereas members of the (often infinite) set of Potential members are not yet operatively available. Introductions may be specified by explicit class system expressions (perhaps as part of interactive sessions) and/or by computational processes.
In some embodiments, a class system expression may declare a member to be an instance of the interpretations of one or more base class expressions, specifying that the member is to satisfy the constraints of the interpretations of the class expressions. Such an Introduction may specify additional attributes of the instance, beyond those specified by its base class expressions and/or provide attribute values for attributes that are not fully determined by its base classes. Instance declarations may ensure specific attribute values for all single-valued attributes of all containing classes, including, for example, those that the class expressions may have specified as abstract and/or specified as limited to the interpretation of a class expressions or to a range of values.
Some embodiments may also allow multi-valued attributes in members.
In some embodiments, users and/or acknowledged Domain experts (or groups of them) may explicitly introduce members. A member description language may be part of, or closely related to one or more class expressions languages. A new, perhaps temporary and/or context-dependent, member might be specified, for example, by providing a declared class name and providing a set of attribute values for the new member.
Any Introduction of a new member to a class (or class system) is conceptually equivalent to adding a new element to its defining Edge class system, for example, declaring a new instance of an Edge class. But it may affect other Edge classes, as well, since the Edge class system may contain expressions relating classes that may require some of their interpretations to include or exclude the added member. Some embodiments may restrict class system expressions in ways that allow such propagation of changes in membership to be performed efficiently. As with several other forms of class system expressions, Introductions potentially introduce contradictions or other kinds of conflicts into a set of class system expressions, which could be dealt with as discussed herein.
Processing a collection of related introductions together (batch data acquisition) may be more efficient than processing them each separately.
In some embodiments, member introductions may contain weights associated with attribute values, which may be used in resolving any conflicts with Inherited attribute values.
In some embodiments, many actual members may be introduced into a class system by analysis of data from outside the PERCos system, for example, and without limitation, accessible databases and/or websites. Data obtained from such sources might not be in the internal form employed by the embodiment, so member assimilation may involve processing items to obtain appropriate internal representations for members. These processes may directly translate to Edge classes and associated attributes and/or be augmented or otherwise determined by member-specific contextual data, and/or, for example, by purpose expression related information.
In some embodiments, the number of possible classes in a class system with N
actual members is 2N. Thus, the addition of a new actual member doubles the potential size of the corresponding class system (but not normally its operational size). This is one of the reasons why embodiments generally declare, enumerate, and/or store explicit representations of only the relatively small portions of class systems that arise during processing.
Members or expressions representing members (or sets thereof) may be resources that can be published for the use of others.
Natural languages and human understanding of languages are frequently ambiguous, particularly in the absence of sufficient context. Consider, for example, the following (actual) newspaper headline:

Red tape holds up new bridge In one interpretation, "red tape" refers to "a narrow flexible strip whose color is red," and "holds up" apparatus and method embodiments "supports." But in another interpretation, "red tape"
refers to "an excessively complex official routine," and "holds up" apparatus and method embodiments "delays."
Even when there is agreement on the meaning of each word in a phrase, there may still be syntactic ambiguity, i.e., different grammatical ways of combining the word senses. Consider, for example:
The skies are not cloudy all day This could mean "it is not true that the skies are cloudy all day," or "it is true all day that the skies are not cloudy." A human reader may use real-world knowledge, common sense, and/or intuition to decide whether to interpret it as meaning that the skies are never cloudy, or that they may sometimes be cloudy, but not all day.
Humans can usually deal with ambiguities in natural languages, because humans are good at resolving ambiguities and associating terms with the correct meanings using context, relational thinking, "common sense," and their knowledge of the world. Still, a human may find it challenging to create natural language statements that may always be precisely and correctly understood, in all contexts, by other humans¨let alone by computers. At a subsequent time, even its creator may no longer understand or remember how to properly interpret some statement.
Computers are not nearly as good as humans at resolving ambiguities, in part because they generally do not adequately include context. Much imprecision in descriptions and interpretations of user classes is due to user processes (in perception, emotion, and thought) that are subjective, relational, impressionistic, and/or imprecise. PERCos embodiments systems are designed, in part, to bridge between imprecision of focus and intent on the human side of the Edge, and the precision that is appropriate on the computing side of the Edge, while retaining the useful lossy characteristics of user classes.
The focus of the PERCos embodiments architecture is not attempting to "understand" what is in the user's head, but responding in ways that optimize user satisfaction through experiences and/or providing other results for satisfying expressed purposes. The PERCos embodiments architecture helps ensure that expressed purposes are supported effectively by identifying and using available resources optimal for those purposes. This is in part achieved by complementary declarations of purpose-related contextual information by both users (what they want) and publishers of resources (what they provide). Somewhat similar "parallel declarations" are currently employed in certain search engine / tagging database implementations, but these implementations fail to provide apparatus and method embodiments for effectively characterizing purpose, for providing structures to meaningfully organize, express, and employ context, and for employing class Structure generalizations that reflect relevant contextual scenarios.
Representing subclass/superclass Relations A subclass relation specifies the set of all pairs of classes such that A is a subclass of B. A
subclass relation's associated lattice may be represented in a variety of ways, including:
1. Boolean matrices, 2. lists of the subclasses of each class, 3. lists of the superclasses of each class, 4. directed graphs relating subclasses and superclasses, and/or 5. an algorithm that, at least in part, computes the relationship.
One useful approach is to declare all applicable direct superclasses as part of each class expression and to add a node (for the class) and one or more Edges (one per superclass) to a directed acyclic graph (DAG) representing the subclass/superclass lattice.
This seems suitable for a practical boundlessly extensible system, and may be used in some PERCos embodiments.

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Claims (9)

WHAT IS CLAIMED IS:
1. A computing method comprising:
receiving, with a computing arrangement, a specification that forms at least one user purpose specification as caused at least in part by a user;
performing a matching or other evaluation process set, between at least a portion of the user purpose specification and at least portions of plural independent stakeholder purpose specifications, specified respectively by plural stakeholders for their resources;
displaying or otherwise providing at least a portion of the matching or other evaluation process set result to the user.
2. The method of claim 1, wherein such user purpose specification comprises, at least in part, at least one verb and at least one domain category, together comprising an approximation of user purpose.
3. The method of claim 1, wherein such matching or other evaluation processing set is performed, at least in part, employing a predetermined classification arrangement established, at least in part, by general or domain specific experts.
4. The method of claim 1, wherein such received specification has been formed, at least in part, employing at least one user purpose related expert created purpose specification.
5. The method of claim 1, wherein at least a portion of such result has been classified as a member of a purpose class.
6. The method of claim 1, wherein at least a portion of the identified resource set is a Contextual Purpose Expression (CPE).
7. The method of claim 1, wherein such user purpose specification includes or uses a Repute purpose assertion specification, wherein such Repute specification information structure includes a persistent asserter/publisher identity, a purpose expression specification, and/or a subject matter identifier.
8. The method of claim 1, wherein performing a matching or other evaluation process set, includes using one or more Repute assertion specifications to determine, at least in part, optimum purpose responsive results.
9. The method of claim 8, wherein such Repute specification information structure includes a persistent asserter/publisher identity, a purpose expression specification, and a subject matter identifier.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI574803B (en) * 2015-06-15 2017-03-21 車樂美縫衣機工業股份有限公司 Robot
US20180349954A1 (en) * 2017-06-06 2018-12-06 Adobe Systems Incorporated Optimizing notification triggers for geo-fence communication systems

Families Citing this family (611)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8677377B2 (en) 2005-09-08 2014-03-18 Apple Inc. Method and apparatus for building an intelligent automated assistant
US8300798B1 (en) 2006-04-03 2012-10-30 Wai Wu Intelligent communication routing system and method
US9318108B2 (en) 2010-01-18 2016-04-19 Apple Inc. Intelligent automated assistant
US8977255B2 (en) 2007-04-03 2015-03-10 Apple Inc. Method and system for operating a multi-function portable electronic device using voice-activation
US10002189B2 (en) 2007-12-20 2018-06-19 Apple Inc. Method and apparatus for searching using an active ontology
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US8996376B2 (en) 2008-04-05 2015-03-31 Apple Inc. Intelligent text-to-speech conversion
US20100030549A1 (en) 2008-07-31 2010-02-04 Lee Michael M Mobile device having human language translation capability with positional feedback
US8676904B2 (en) 2008-10-02 2014-03-18 Apple Inc. Electronic devices with voice command and contextual data processing capabilities
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US20120311585A1 (en) 2011-06-03 2012-12-06 Apple Inc. Organizing task items that represent tasks to perform
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US8731819B2 (en) * 2009-06-10 2014-05-20 Ancestralhunt Partners, Llc System and method for the collaborative collection, assignment, visualization, analysis, and modification of probable genealogical relationships based on geo-spatial and temporal proximity
US9135215B1 (en) * 2009-09-21 2015-09-15 Tilera Corporation Route prediction in packet switched networks
US10276170B2 (en) 2010-01-18 2019-04-30 Apple Inc. Intelligent automated assistant
US8682667B2 (en) 2010-02-25 2014-03-25 Apple Inc. User profiling for selecting user specific voice input processing information
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US9467494B1 (en) 2011-12-30 2016-10-11 Rupaka Mahalingaiah Method and apparatus for enabling mobile cluster computing
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US10417037B2 (en) 2012-05-15 2019-09-17 Apple Inc. Systems and methods for integrating third party services with a digital assistant
US9721563B2 (en) 2012-06-08 2017-08-01 Apple Inc. Name recognition system
US9547647B2 (en) 2012-09-19 2017-01-17 Apple Inc. Voice-based media searching
US10270709B2 (en) 2015-06-26 2019-04-23 Microsoft Technology Licensing, Llc Allocating acceleration component functionality for supporting services
US8959151B1 (en) * 2012-10-04 2015-02-17 Google Inc. Establishing per-page multi-party communication sessions
US20140122695A1 (en) * 2012-10-31 2014-05-01 Rawllin International Inc. Dynamic resource allocation for network content delivery
JP5895823B2 (en) * 2012-11-12 2016-03-30 富士ゼロックス株式会社 Attribute information giving program and attribute information giving device
US9253652B1 (en) * 2013-01-15 2016-02-02 Sprint Communications Company L.P. Ad hoc formation of a swarm for information collection and distribution
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US10652394B2 (en) 2013-03-14 2020-05-12 Apple Inc. System and method for processing voicemail
US9378065B2 (en) 2013-03-15 2016-06-28 Advanced Elemental Technologies, Inc. Purposeful computing
US10748529B1 (en) 2013-03-15 2020-08-18 Apple Inc. Voice activated device for use with a voice-based digital assistant
FR3003984A1 (en) * 2013-03-29 2014-10-03 France Telecom CONDITIONED METHOD OF SHARING FACETS OF USERS AND SHARING SERVER FOR IMPLEMENTING THE METHOD
WO2014197334A2 (en) 2013-06-07 2014-12-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
WO2014197335A1 (en) 2013-06-08 2014-12-11 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
CN110442699A (en) 2013-06-09 2019-11-12 苹果公司 Operate method, computer-readable medium, electronic equipment and the system of digital assistants
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
WO2014209258A1 (en) * 2013-06-24 2014-12-31 Intel Corporation Contextual display apparatus and methods
EP3020020A4 (en) * 2013-07-10 2016-12-21 Ifthisthen Inc Systems and methods for knowledge management
EP3019971B1 (en) * 2013-07-12 2020-05-06 Google LLC Methods and systems for performance monitoring for mobile applications
US20150019301A1 (en) * 2013-07-12 2015-01-15 Xerox Corporation System and method for cloud capability estimation for user application in black-box environments using benchmark-based approximation
US10242091B2 (en) * 2013-08-08 2019-03-26 Systamedic, Inc. Method of knowledge extraction through data mining
US10970183B1 (en) * 2013-08-16 2021-04-06 The Mathworks, Inc. System and method for improving model performance
US9053392B2 (en) * 2013-08-28 2015-06-09 Adobe Systems Incorporated Generating a hierarchy of visual pattern classes
US20150073958A1 (en) * 2013-09-12 2015-03-12 Bank Of America Corporation RESEARCH REPORT RECOMMENDATION ENGINE ("R+hu 3 +lE")
US20150095320A1 (en) * 2013-09-27 2015-04-02 Trooclick France Apparatus, systems and methods for scoring the reliability of online information
US9524510B2 (en) 2013-10-02 2016-12-20 Turn Inc. Adaptive fuzzy fallback stratified sampling for fast reporting and forecasting
WO2015059837A1 (en) * 2013-10-25 2015-04-30 楽天株式会社 Information processing system, information processing system control method, information processing device, information processing device control method, program, and information storage medium
EP3063663A4 (en) 2013-10-30 2017-04-19 Hewlett-Packard Enterprise Development LP Stitching an application model to an infrastructure template
US10230580B2 (en) 2013-10-30 2019-03-12 Hewlett Packard Enterprise Development Lp Management of the lifecycle of a cloud service modeled as a topology
EP3063660A4 (en) 2013-10-30 2017-06-14 Hewlett-Packard Enterprise Development LP Execution of a topology
WO2015065356A1 (en) 2013-10-30 2015-05-07 Hewlett-Packard Development Company, L.P. Topology remediation
WO2015065370A1 (en) 2013-10-30 2015-05-07 Hewlett-Packard Development Company, L.P. Monitoring a cloud service modeled as a topology
US10284427B2 (en) * 2013-10-30 2019-05-07 Hewlett Packard Enterprise Development Lp Managing the lifecycle of a cloud service modeled as topology decorated by a number of policies
US20150127593A1 (en) * 2013-11-06 2015-05-07 Forever Identity, Inc. Platform to Acquire and Represent Human Behavior and Physical Traits to Achieve Digital Eternity
US9288220B2 (en) * 2013-11-07 2016-03-15 Cyberpoint International Llc Methods and systems for malware detection
US20150161236A1 (en) * 2013-12-05 2015-06-11 Lenovo (Singapore) Pte. Ltd. Recording context for conducting searches
US10296160B2 (en) 2013-12-06 2019-05-21 Apple Inc. Method for extracting salient dialog usage from live data
US10138717B1 (en) * 2014-01-07 2018-11-27 Novi Labs, LLC Predicting well performance with feature similarity
US9654571B2 (en) 2014-01-21 2017-05-16 Time Warner Cable Enterprises Llc Publish-subscribe messaging in a content network
US9652549B2 (en) * 2014-02-05 2017-05-16 International Business Machines Corporation Capturing and managing knowledge from social networking interactions
US9703611B1 (en) * 2014-03-21 2017-07-11 Amazon Technologies, Inc. Isolating resources for utilization by tenants executing in multi-tenant software containers
US9754122B1 (en) 2014-03-21 2017-09-05 Amazon Technologies, Inc. Isolating tenants executing in multi-tenant software containers
US9471353B1 (en) 2014-03-21 2016-10-18 Amazon Technologies, Inc. Isolating tenants executing in multi-tenant software containers
US11151460B2 (en) 2014-03-26 2021-10-19 Unanimous A. I., Inc. Adaptive population optimization for amplifying the intelligence of crowds and swarms
US11941239B2 (en) 2014-03-26 2024-03-26 Unanimous A.I., Inc. System and method for enhanced collaborative forecasting
US11269502B2 (en) 2014-03-26 2022-03-08 Unanimous A. I., Inc. Interactive behavioral polling and machine learning for amplification of group intelligence
US10817159B2 (en) 2014-03-26 2020-10-27 Unanimous A. I., Inc. Non-linear probabilistic wagering for amplified collective intelligence
US10817158B2 (en) 2014-03-26 2020-10-27 Unanimous A. I., Inc. Method and system for a parallel distributed hyper-swarm for amplifying human intelligence
US10817884B2 (en) * 2014-05-08 2020-10-27 Google Llc Building topic-oriented audiences
US9286056B2 (en) * 2014-05-19 2016-03-15 International Business Machines Corporation Reducing storage facility code load suspend rate by redundancy check
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
EP3480811A1 (en) 2014-05-30 2019-05-08 Apple Inc. Multi-command single utterance input method
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US20150356117A1 (en) * 2014-06-09 2015-12-10 Oracle International Corporation Eventual consistency to resolve subscriber sharing relationships in a distributed system
US10325205B2 (en) * 2014-06-09 2019-06-18 Cognitive Scale, Inc. Cognitive information processing system environment
CN105323186B (en) * 2014-06-20 2020-04-21 中兴通讯股份有限公司 Notification message load control method and device
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US20160019505A1 (en) * 2014-07-15 2016-01-21 Apollo Education Group, Inc. Combining real-time labor market data with career interest recommendations for optimal career selection
US10572935B1 (en) * 2014-07-16 2020-02-25 Intuit, Inc. Disambiguation of entities based on financial interactions
US20160191483A1 (en) * 2014-07-18 2016-06-30 Donald Larson Universal Connector
US20160026941A1 (en) * 2014-07-26 2016-01-28 International Business Machines Corporation Updating and synchronizing existing case instances in response to solution design changes
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US20160080422A1 (en) * 2014-09-12 2016-03-17 International Business Machines Corporation Transforming business policies to information technology security control terms for improved system compliance
US20160085738A1 (en) * 2014-09-24 2016-03-24 Microsoft Technology Licensing, Llc Cloud-Based Parallel Computation Using Actor Modules
US10530790B2 (en) 2014-09-25 2020-01-07 Oracle International Corporation Privileged session analytics
US10482404B2 (en) * 2014-09-25 2019-11-19 Oracle International Corporation Delegated privileged access grants
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US10489213B2 (en) * 2014-10-01 2019-11-26 Red Hat, Inc. Execution of a method at a cluster of nodes
TWI612431B (en) * 2014-10-03 2018-01-21 物聯智慧科技(深圳)有限公司 Searching system, method and p2p device for p2p device community
US10474680B2 (en) 2014-10-09 2019-11-12 Splunk Inc. Automatic entity definitions
US11455590B2 (en) 2014-10-09 2022-09-27 Splunk Inc. Service monitoring adaptation for maintenance downtime
US11755559B1 (en) 2014-10-09 2023-09-12 Splunk Inc. Automatic entity control in a machine data driven service monitoring system
US10305758B1 (en) 2014-10-09 2019-05-28 Splunk Inc. Service monitoring interface reflecting by-service mode
US11501238B2 (en) 2014-10-09 2022-11-15 Splunk Inc. Per-entity breakdown of key performance indicators
US9158811B1 (en) 2014-10-09 2015-10-13 Splunk, Inc. Incident review interface
US9146962B1 (en) 2014-10-09 2015-09-29 Splunk, Inc. Identifying events using informational fields
US10193775B2 (en) 2014-10-09 2019-01-29 Splunk Inc. Automatic event group action interface
US9491059B2 (en) 2014-10-09 2016-11-08 Splunk Inc. Topology navigator for IT services
US9584374B2 (en) 2014-10-09 2017-02-28 Splunk Inc. Monitoring overall service-level performance using an aggregate key performance indicator derived from machine data
US11671312B2 (en) 2014-10-09 2023-06-06 Splunk Inc. Service detail monitoring console
US9760240B2 (en) 2014-10-09 2017-09-12 Splunk Inc. Graphical user interface for static and adaptive thresholds
US11200130B2 (en) 2015-09-18 2021-12-14 Splunk Inc. Automatic entity control in a machine data driven service monitoring system
US11087263B2 (en) 2014-10-09 2021-08-10 Splunk Inc. System monitoring with key performance indicators from shared base search of machine data
US10536353B2 (en) 2014-10-09 2020-01-14 Splunk Inc. Control interface for dynamic substitution of service monitoring dashboard source data
US10209956B2 (en) 2014-10-09 2019-02-19 Splunk Inc. Automatic event group actions
US10417225B2 (en) 2015-09-18 2019-09-17 Splunk Inc. Entity detail monitoring console
US9146954B1 (en) 2014-10-09 2015-09-29 Splunk, Inc. Creating entity definition from a search result set
US10505825B1 (en) 2014-10-09 2019-12-10 Splunk Inc. Automatic creation of related event groups for IT service monitoring
US10417108B2 (en) 2015-09-18 2019-09-17 Splunk Inc. Portable control modules in a machine data driven service monitoring system
US10235638B2 (en) 2014-10-09 2019-03-19 Splunk Inc. Adaptive key performance indicator thresholds
US9210056B1 (en) 2014-10-09 2015-12-08 Splunk Inc. Service monitoring interface
US9130832B1 (en) 2014-10-09 2015-09-08 Splunk, Inc. Creating entity definition from a file
US9247021B1 (en) 2014-11-07 2016-01-26 Open Text S.A. System, method and architecture for a document as a node on a social graph
EP3023919A1 (en) * 2014-11-20 2016-05-25 Tata Consultancy Services Ltd. Method and system for efficent transition of information technology operations
US20160148251A1 (en) * 2014-11-24 2016-05-26 Adobe Systems Incorporated Risk Quantification for Policy Deployment
US9886296B2 (en) * 2014-12-01 2018-02-06 International Business Machines Corporation Managing hypervisor weights in a virtual environment
US20170262911A1 (en) * 2014-12-05 2017-09-14 Hewlett Packard Enterprise Development Lp Cloud service rating
US9876713B2 (en) * 2014-12-31 2018-01-23 International Business Machines Corporation Cross-domain service request placement in a software defined environment (SDE)
US9678790B2 (en) * 2015-01-07 2017-06-13 Qualcomm Incorporated Devices and methods implementing operations for selective enforcement of task dependencies
US10198155B2 (en) 2015-01-31 2019-02-05 Splunk Inc. Interface for automated service discovery in I.T. environments
US9967351B2 (en) 2015-01-31 2018-05-08 Splunk Inc. Automated service discovery in I.T. environments
US10528598B2 (en) * 2015-02-26 2020-01-07 Schneider Electric USA, Inc. Energy management system and method
US10152299B2 (en) 2015-03-06 2018-12-11 Apple Inc. Reducing response latency of intelligent automated assistants
US10567477B2 (en) 2015-03-08 2020-02-18 Apple Inc. Virtual assistant continuity
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US10630686B2 (en) * 2015-03-12 2020-04-21 Fornetix Llc Systems and methods for organizing devices in a policy hierarchy
US10965459B2 (en) 2015-03-13 2021-03-30 Fornetix Llc Server-client key escrow for applied key management system and process
US10496692B1 (en) * 2015-03-17 2019-12-03 Amazon Technologies, Inc. Resource tagging and grouping
IN2015CH01317A (en) * 2015-03-18 2015-04-10 Wipro Ltd
US20160300190A1 (en) * 2015-04-08 2016-10-13 Chequed.com, Inc. Performance evaluation system
US9592828B2 (en) * 2015-04-13 2017-03-14 Nec Corporation Long term driving danger prediction system
US10989838B2 (en) * 2015-04-14 2021-04-27 Utopus Insights, Inc. Weather-driven multi-category infrastructure impact forecasting
US9652327B2 (en) 2015-04-17 2017-05-16 Microsoft Technology Licensing, Llc Restoring service acceleration
US9792154B2 (en) 2015-04-17 2017-10-17 Microsoft Technology Licensing, Llc Data processing system having a hardware acceleration plane and a software plane
US10511478B2 (en) 2015-04-17 2019-12-17 Microsoft Technology Licensing, Llc Changing between different roles at acceleration components
US10198294B2 (en) 2015-04-17 2019-02-05 Microsoft Licensing Technology, LLC Handling tenant requests in a system that uses hardware acceleration components
US10296392B2 (en) 2015-04-17 2019-05-21 Microsoft Technology Licensing, Llc Implementing a multi-component service using plural hardware acceleration components
US11461208B1 (en) 2015-04-24 2022-10-04 Tanium Inc. Reliable map-reduce communications in a decentralized, self-organizing communication orbit of a distributed network
US10460227B2 (en) 2015-05-15 2019-10-29 Apple Inc. Virtual assistant in a communication session
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10200824B2 (en) 2015-05-27 2019-02-05 Apple Inc. Systems and methods for proactively identifying and surfacing relevant content on a touch-sensitive device
US10642843B2 (en) * 2015-05-28 2020-05-05 Google Llc World knowledge triggers
US10204382B2 (en) 2015-05-29 2019-02-12 Intuit Inc. Method and system for identifying users who benefit from filing itemized deductions to reduce an average time consumed for users preparing tax returns with a tax return preparation system
US9900275B2 (en) * 2015-06-01 2018-02-20 Apple Inc. Tracking object across processes
US9578173B2 (en) 2015-06-05 2017-02-21 Apple Inc. Virtual assistant aided communication with 3rd party service in a communication session
US11025565B2 (en) 2015-06-07 2021-06-01 Apple Inc. Personalized prediction of responses for instant messaging
US10216555B2 (en) 2015-06-26 2019-02-26 Microsoft Technology Licensing, Llc Partially reconfiguring acceleration components
US20160378747A1 (en) 2015-06-29 2016-12-29 Apple Inc. Virtual assistant for media playback
US10956880B2 (en) * 2015-07-01 2021-03-23 Paypal, Inc. Mixed deployment architecture for distributed services
US10061766B2 (en) * 2015-07-27 2018-08-28 Texas State Technical College System Systems and methods for domain-specific machine-interpretation of input data
US10169828B1 (en) 2015-07-29 2019-01-01 Intuit Inc. Method and system for applying analytics models to a tax return preparation system to determine a likelihood of receiving earned income tax credit by a user
US10769212B2 (en) * 2015-07-31 2020-09-08 Netapp Inc. Extensible and elastic data management services engine external to a storage domain
US10620802B1 (en) * 2015-08-10 2020-04-14 Cadence Design Systems, Inc. Algorithmic modeling interface process
US20170063916A1 (en) * 2015-08-26 2017-03-02 Wegilant Net Solutions Private Limited System and method for automatically identifying broken authentication and other related vulnerabilities in web services
US20170063708A1 (en) * 2015-09-01 2017-03-02 International Business Machines Corporation Resource exchange service transaction for cloud computing
US10671428B2 (en) 2015-09-08 2020-06-02 Apple Inc. Distributed personal assistant
US10747498B2 (en) 2015-09-08 2020-08-18 Apple Inc. Zero latency digital assistant
US10740384B2 (en) 2015-09-08 2020-08-11 Apple Inc. Intelligent automated assistant for media search and playback
US10331312B2 (en) 2015-09-08 2019-06-25 Apple Inc. Intelligent automated assistant in a media environment
US10896377B2 (en) * 2015-09-10 2021-01-19 International Business Machines Corporation Categorizing concept terms for game-based training in cognitive computing systems
US11188844B2 (en) 2015-09-10 2021-11-30 International Business Machines Corporation Game-based training for cognitive computing systems
US10564794B2 (en) * 2015-09-15 2020-02-18 Xerox Corporation Method and system for document management considering location, time and social context
US10482231B1 (en) * 2015-09-22 2019-11-19 Amazon Technologies, Inc. Context-based access controls
US10387209B2 (en) * 2015-09-28 2019-08-20 International Business Machines Corporation Dynamic transparent provisioning of resources for application specific resources
US11010550B2 (en) 2015-09-29 2021-05-18 Apple Inc. Unified language modeling framework for word prediction, auto-completion and auto-correction
US10366158B2 (en) 2015-09-29 2019-07-30 Apple Inc. Efficient word encoding for recurrent neural network language models
US20170091612A1 (en) * 2015-09-30 2017-03-30 Apple Inc. Proactive assistant with memory assistance
EP3361853A4 (en) 2015-10-12 2019-06-19 Drone Seed Co. Forestry information management systems and methods streamlined by automatic biometric data prioritization
US10212876B2 (en) 2015-10-12 2019-02-26 Droneseed Co. Aerial deployment planting methods and systems
US10157351B1 (en) * 2015-10-20 2018-12-18 Amazon Technologies, Inc. Persona based data mining system
US10346802B2 (en) * 2015-10-28 2019-07-09 Open Text GXS ULC Trading partner relationship graph for information exchange platform
US10387787B1 (en) 2015-10-28 2019-08-20 Intuit Inc. Method and system for providing personalized user experiences to software system users
US9891792B1 (en) * 2015-10-30 2018-02-13 Intuit Inc. Method and system for building and utilizing interactive software system predictive models using biometric data
US10657180B2 (en) * 2015-11-04 2020-05-19 International Business Machines Corporation Building and reusing solution cache for constraint satisfaction problems
US10691473B2 (en) 2015-11-06 2020-06-23 Apple Inc. Intelligent automated assistant in a messaging environment
US10956666B2 (en) 2015-11-09 2021-03-23 Apple Inc. Unconventional virtual assistant interactions
US10102282B2 (en) * 2015-11-18 2018-10-16 University-Industry Cooperation Foundation Of Kyung Hee University Apparatus for mediation bridge ontology based on ontology alignment pattern
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10019292B2 (en) * 2015-12-02 2018-07-10 Fts Computertechnik Gmbh Method for executing a comprehensive real-time computer application by exchanging time-triggered messages among real-time software components
US10013450B2 (en) 2015-12-03 2018-07-03 International Business Machines Corporation Using knowledge graphs to identify potential inconsistencies in works of authorship
US10013404B2 (en) 2015-12-03 2018-07-03 International Business Machines Corporation Targeted story summarization using natural language processing
US10248738B2 (en) 2015-12-03 2019-04-02 International Business Machines Corporation Structuring narrative blocks in a logical sequence
US10320897B2 (en) * 2015-12-15 2019-06-11 Microsoft Technology Licensing, Llc Automatic system response to external field-replaceable unit (FRU) process
US10120939B2 (en) 2015-12-16 2018-11-06 At&T Intellectual Property I, L.P. Detecting and using mood-condition affinities
WO2017108850A1 (en) * 2015-12-21 2017-06-29 Koninklijke Philips N.V. System and method for effectuating presentation of content based on complexity of content segments therein
US10204384B2 (en) * 2015-12-21 2019-02-12 Mcafee, Llc Data loss prevention of social media content
US9622180B1 (en) * 2015-12-23 2017-04-11 Intel Corporation Wearable device command regulation
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US10817593B1 (en) * 2015-12-29 2020-10-27 Wells Fargo Bank, N.A. User information gathering and distribution system
US9843941B2 (en) * 2015-12-31 2017-12-12 Kodacloud Inc. Delaying execution of a corrective action in a wireless environment
US10354201B1 (en) * 2016-01-07 2019-07-16 Amazon Technologies, Inc. Scalable clustering for mixed machine learning data
US10373064B2 (en) 2016-01-08 2019-08-06 Intuit Inc. Method and system for adjusting analytics model characteristics to reduce uncertainty in determining users' preferences for user experience options, to support providing personalized user experiences to users with a software system
US10861106B1 (en) 2016-01-14 2020-12-08 Intuit Inc. Computer generated user interfaces, computerized systems and methods and articles of manufacture for personalizing standardized deduction or itemized deduction flow determinations
US11069001B1 (en) 2016-01-15 2021-07-20 Intuit Inc. Method and system for providing personalized user experiences in compliance with service provider business rules
US10303517B1 (en) 2016-01-28 2019-05-28 BrainFights, Inc. Automated evaluation of computer programming
US11650903B2 (en) 2016-01-28 2023-05-16 Codesignal, Inc. Computer programming assessment
US11030631B1 (en) 2016-01-29 2021-06-08 Intuit Inc. Method and system for generating user experience analytics models by unbiasing data samples to improve personalization of user experiences in a tax return preparation system
US10204116B2 (en) * 2016-02-08 2019-02-12 Corelogic Solutions, Llc Image metadata enrichment generator
US10860086B2 (en) 2016-02-26 2020-12-08 Fornetix Llc Policy-enabled encryption keys having complex logical operations
US10880281B2 (en) 2016-02-26 2020-12-29 Fornetix Llc Structure of policies for evaluating key attributes of encryption keys
CN105589561B (en) * 2016-03-01 2018-01-30 探客柏瑞科技(北京)有限公司 A kind of measurement in real time and the device of feedback interpersonal communication efficiency
US11886229B1 (en) 2016-03-08 2024-01-30 Tanium Inc. System and method for generating a global dictionary and performing similarity search queries in a network
US11609835B1 (en) * 2016-03-08 2023-03-21 Tanium Inc. Evaluating machine and process performance in distributed system
US10446143B2 (en) 2016-03-14 2019-10-15 Apple Inc. Identification of voice inputs providing credentials
CN107203557A (en) * 2016-03-17 2017-09-26 伊姆西公司 The method and device of object to be searched for handling
US10432650B2 (en) 2016-03-31 2019-10-01 Stuart Staniford System and method to protect a webserver against application exploits and attacks
US10796238B2 (en) * 2016-04-07 2020-10-06 Cognitive Scale, Inc. Cognitive personal assistant
US10733518B2 (en) * 2016-04-07 2020-08-04 Cognitive Scale, Inc. Cognitive personal procurement assistant
US10621597B2 (en) 2016-04-15 2020-04-14 Intuit Inc. Method and system for updating analytics models that are used to dynamically and adaptively provide personalized user experiences in a software system
EP3236668A1 (en) * 2016-04-18 2017-10-25 ABB Schweiz AG Method and system for reproducing an instrument`s calibration certificate
CN106055028B (en) * 2016-04-19 2023-05-26 杭州纳雄科技有限公司 Restructurable intelligent wearable device and control method thereof
US10621677B2 (en) 2016-04-25 2020-04-14 Intuit Inc. Method and system for applying dynamic and adaptive testing techniques to a software system to improve selection of predictive models for personalizing user experiences in the software system
US10652303B2 (en) * 2016-04-28 2020-05-12 Rabbit Asset Purchase Corp. Screencast orchestration
US9983859B2 (en) 2016-04-29 2018-05-29 Intuit Inc. Method and system for developing and deploying data science transformations from a development computing environment into a production computing environment
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US10409876B2 (en) * 2016-05-26 2019-09-10 Microsoft Technology Licensing, Llc. Intelligent capture, storage, and retrieval of information for task completion
US11429832B2 (en) * 2016-06-02 2022-08-30 Kodak Alaris Inc. System and method for predictive curation, production infrastructure, and personal content assistant
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US10346927B1 (en) 2016-06-06 2019-07-09 Intuit Inc. Method and system for providing a personalized user experience in a tax return preparation system based on predicted life events for a user
US11227589B2 (en) 2016-06-06 2022-01-18 Apple Inc. Intelligent list reading
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US11842313B1 (en) * 2016-06-07 2023-12-12 Lockheed Martin Corporation Method, system and computer-readable storage medium for conducting on-demand human performance assessments using unstructured data from multiple sources
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
DK179309B1 (en) 2016-06-09 2018-04-23 Apple Inc Intelligent automated assistant in a home environment
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10490187B2 (en) 2016-06-10 2019-11-26 Apple Inc. Digital assistant providing automated status report
US10509862B2 (en) 2016-06-10 2019-12-17 Apple Inc. Dynamic phrase expansion of language input
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10586535B2 (en) 2016-06-10 2020-03-10 Apple Inc. Intelligent digital assistant in a multi-tasking environment
DK201670540A1 (en) 2016-06-11 2018-01-08 Apple Inc Application integration with a digital assistant
DK179049B1 (en) 2016-06-11 2017-09-18 Apple Inc Data driven natural language event detection and classification
DK179343B1 (en) 2016-06-11 2018-05-14 Apple Inc Intelligent task discovery
DK179415B1 (en) 2016-06-11 2018-06-14 Apple Inc Intelligent device arbitration and control
AU2017100670C4 (en) 2016-06-12 2019-11-21 Apple Inc. User interfaces for retrieving contextually relevant media content
US10038602B2 (en) * 2016-06-13 2018-07-31 International Business Machines Corporation Monitoring resource consumption based on fixed cost for threshold use and additional cost for use above the threshold
CN106126592B (en) * 2016-06-20 2021-09-14 北京小米移动软件有限公司 Processing method and device for search data
US11222266B2 (en) * 2016-07-15 2022-01-11 Intuit Inc. System and method for automatic learning of functions
US10579721B2 (en) 2016-07-15 2020-03-03 Intuit Inc. Lean parsing: a natural language processing system and method for parsing domain-specific languages
US11049190B2 (en) 2016-07-15 2021-06-29 Intuit Inc. System and method for automatically generating calculations for fields in compliance forms
US20180018311A1 (en) * 2016-07-15 2018-01-18 Intuit Inc. Method and system for automatically extracting relevant tax terms from forms and instructions
US10725896B2 (en) 2016-07-15 2020-07-28 Intuit Inc. System and method for identifying a subset of total historical users of a document preparation system to represent a full set of test scenarios based on code coverage
US10241985B2 (en) 2016-08-02 2019-03-26 Open Text Sa Ulc Systems and methods for intelligent document-centric orchestration through information exchange platform
US10223234B2 (en) * 2016-08-15 2019-03-05 Microsoft Technology Licensing, Llc Monitoring a web application using an outside-in strategy
US10484382B2 (en) * 2016-08-31 2019-11-19 Oracle International Corporation Data management for a multi-tenant identity cloud service
US10474753B2 (en) 2016-09-07 2019-11-12 Apple Inc. Language identification using recurrent neural networks
JP6852321B2 (en) * 2016-09-09 2021-03-31 コニカミノルタ株式会社 Workflow management device and control program for workflow management device
CN107018168B (en) 2016-09-19 2020-07-24 阿里巴巴集团控股有限公司 Internet resource scheduling method and device and network red packet scheduling method
JP6738703B2 (en) * 2016-09-20 2020-08-12 株式会社日立製作所 Impact influence analysis method and apparatus
US10666569B1 (en) 2016-09-23 2020-05-26 Amazon Technologies, Inc. Journal service with named clients
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant
US10805238B1 (en) 2016-09-23 2020-10-13 Amazon Technologies, Inc. Management of alternative resources
US10423459B1 (en) * 2016-09-23 2019-09-24 Amazon Technologies, Inc. Resource manager
US10942946B2 (en) 2016-09-26 2021-03-09 Splunk, Inc. Automatic triage model execution in machine data driven monitoring automation apparatus
US11024044B2 (en) * 2016-09-26 2021-06-01 Digitalglobe, Inc. Techniques for image co-registration
US10853887B2 (en) * 2016-09-27 2020-12-01 Adobe Inc. Determination of paywall metrics
US10769561B2 (en) * 2016-10-12 2020-09-08 Accenture Global Solutions Limited Adaptive logistics platform for generating and updating schedules using natural language processing
CN106647355B (en) * 2016-11-09 2023-11-07 中国民用航空飞行学院 Data processing method and system for flight scenario environment evaluation
CN106453059B (en) * 2016-11-11 2019-11-12 王柯 A kind of realization method and system of group's template
US20190156348A1 (en) * 2017-11-21 2019-05-23 David Levy Market-based Fact Verification Media System and Method
DE102016223193A1 (en) * 2016-11-23 2018-05-24 Fujitsu Limited Method and apparatus for completing a knowledge graph
US10567248B2 (en) 2016-11-29 2020-02-18 Intel Corporation Distributed assignment of video analytics tasks in cloud computing environments to reduce bandwidth utilization
CN106779817A (en) * 2016-11-29 2017-05-31 竹间智能科技(上海)有限公司 Intension recognizing method and system based on various dimensions information
US11281993B2 (en) 2016-12-05 2022-03-22 Apple Inc. Model and ensemble compression for metric learning
US10303335B2 (en) 2016-12-08 2019-05-28 Bank Of America Corporation Multicomputer processing of client device request data with centralized event orchestration
US10440102B2 (en) 2016-12-08 2019-10-08 Bank Of America Corporation Multicomputer processing of client device request data using centralized event orchestrator and dynamic endpoint engine
US10298575B2 (en) 2016-12-08 2019-05-21 Bank Of America Corporation Multicomputer processing of an event authentication request with centralized event orchestration
US10264056B2 (en) 2016-12-08 2019-04-16 Bank Of America Corporation Multicomputer processing of an event request from an event origination device with centralized event orchestration
US10296882B2 (en) 2016-12-08 2019-05-21 Bank Of America Corporation Multicomputer processing of client device request data using centralized event orchestrator and link discovery engine
US10216830B2 (en) 2016-12-08 2019-02-26 Bank Of America Corporation Multicomputer processing of client device request data using centralized event orchestrator and link discovery engine
US10310712B2 (en) 2016-12-08 2019-06-04 Bank Of America Corporation Multicomputer processing of client device request data with centralized event orchestration
US10217087B2 (en) 2016-12-08 2019-02-26 Bank Of America Corporation Multicomputer processing of client device request data using centralized event orchestrator
US10733041B2 (en) * 2016-12-15 2020-08-04 Nutanix, Inc. System, method and computer program product for providing status information during execution of a process to manage resource state enforcement
US10320636B2 (en) 2016-12-21 2019-06-11 Ca, Inc. State information completion using context graphs
US10394960B2 (en) * 2016-12-21 2019-08-27 Facebook, Inc. Transliteration decoding using a tree structure
US10423647B2 (en) * 2016-12-21 2019-09-24 Ca, Inc. Descriptive datacenter state comparison
US10346450B2 (en) 2016-12-21 2019-07-09 Ca, Inc. Automatic datacenter state summarization
US10593346B2 (en) 2016-12-22 2020-03-17 Apple Inc. Rank-reduced token representation for automatic speech recognition
GB2558220B (en) 2016-12-22 2019-05-15 Advanced Risc Mach Ltd Vector generating instruction
US10191836B2 (en) * 2016-12-28 2019-01-29 Nxp Usa, Inc. Software watchpoints apparatus for variables stored in registers
US10223536B2 (en) * 2016-12-29 2019-03-05 Paypal, Inc. Device monitoring policy
US10747512B2 (en) * 2017-01-06 2020-08-18 International Business Machines Corporation Partial object instantiation for object oriented applications
US11204787B2 (en) 2017-01-09 2021-12-21 Apple Inc. Application integration with a digital assistant
DE102018100730A1 (en) * 2017-01-13 2018-07-19 Evghenii GABUROV Execution of calculation graphs
US10200914B2 (en) * 2017-01-20 2019-02-05 Microsoft Technology Licensing, Llc Responsive quality of service management
EP3358898B1 (en) * 2017-02-07 2021-04-28 Volkswagen Aktiengesellschaft Apparatuses, methods and computer programs for allocating transmission resources and for a mobile transceiver
KR102018795B1 (en) * 2017-02-08 2019-09-05 구글 엘엘씨 Ergonomic Evaluation Garments
US10498477B2 (en) * 2017-02-15 2019-12-03 Qualcomm Incorporated Tracking reference signal configuration design
US20180247371A1 (en) * 2017-02-24 2018-08-30 Michael Saigh Geometrical Rarity Correlation, Venttinization and Protection System and Toolkit
US10943309B1 (en) 2017-03-10 2021-03-09 Intuit Inc. System and method for providing a predicted tax refund range based on probabilistic calculation
US10410133B2 (en) 2017-03-22 2019-09-10 At&T Intellectual Property I, L.P. Methods, devices and systems for managing network video traffic
US11049005B2 (en) 2017-03-22 2021-06-29 At&T Intellectual Property I, L.P. Methods, devices and systems for managing network video traffic
CN107085541A (en) * 2017-03-31 2017-08-22 西藏喜年通讯科技有限公司 Method, mobile device and the device of the information interaction of different application platforms
US10579121B2 (en) * 2017-04-01 2020-03-03 Intel Corporation Processor power management
CN107256224B (en) * 2017-04-28 2018-10-09 北京神州泰岳软件股份有限公司 A kind of generation method of the element structure of knowledge, searching method, apparatus and system
US10417266B2 (en) 2017-05-09 2019-09-17 Apple Inc. Context-aware ranking of intelligent response suggestions
DK201770383A1 (en) 2017-05-09 2018-12-14 Apple Inc. User interface for correcting recognition errors
DK201770439A1 (en) 2017-05-11 2018-12-13 Apple Inc. Offline personal assistant
US10395654B2 (en) 2017-05-11 2019-08-27 Apple Inc. Text normalization based on a data-driven learning network
US10726832B2 (en) 2017-05-11 2020-07-28 Apple Inc. Maintaining privacy of personal information
DK180048B1 (en) 2017-05-11 2020-02-04 Apple Inc. MAINTAINING THE DATA PROTECTION OF PERSONAL INFORMATION
DK179745B1 (en) 2017-05-12 2019-05-01 Apple Inc. SYNCHRONIZATION AND TASK DELEGATION OF A DIGITAL ASSISTANT
US10491465B2 (en) 2017-05-12 2019-11-26 Dell Products L.P. System and method for dynamic and extensible management of device nodes
DK201770428A1 (en) 2017-05-12 2019-02-18 Apple Inc. Low-latency intelligent automated assistant
DK179496B1 (en) 2017-05-12 2019-01-15 Apple Inc. USER-SPECIFIC Acoustic Models
US11301477B2 (en) 2017-05-12 2022-04-12 Apple Inc. Feedback analysis of a digital assistant
DK201770432A1 (en) 2017-05-15 2018-12-21 Apple Inc. Hierarchical belief states for digital assistants
DK201770431A1 (en) 2017-05-15 2018-12-20 Apple Inc. Optimizing dialogue policy decisions for digital assistants using implicit feedback
US20180336275A1 (en) 2017-05-16 2018-11-22 Apple Inc. Intelligent automated assistant for media exploration
US10403278B2 (en) 2017-05-16 2019-09-03 Apple Inc. Methods and systems for phonetic matching in digital assistant services
US10311144B2 (en) 2017-05-16 2019-06-04 Apple Inc. Emoji word sense disambiguation
DK179549B1 (en) 2017-05-16 2019-02-12 Apple Inc. Far-field extension for digital assistant services
US20180336892A1 (en) 2017-05-16 2018-11-22 Apple Inc. Detecting a trigger of a digital assistant
CN108965898B (en) * 2017-05-19 2020-08-04 武汉斗鱼网络科技有限公司 Method, storage medium and system for preventing harassment in continuous wheat
EP3631644B8 (en) * 2017-06-02 2022-07-20 Thinkspan, LLC Universal data scaffold based data management platform
US10657328B2 (en) 2017-06-02 2020-05-19 Apple Inc. Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling
US10567356B2 (en) 2017-06-20 2020-02-18 Microsoft Technology Licensing, Llc Monitoring cloud computing environments with data control policies
US10762218B2 (en) 2017-06-20 2020-09-01 Microsoft Technology Licensing, Llc Network buildout for cloud computing environments with data control policies
CN107247794B (en) * 2017-06-21 2020-12-04 北京小米移动软件有限公司 Topic guiding method in live broadcast, live broadcast device and terminal equipment
CN107391584B (en) * 2017-06-22 2020-12-11 中南大学 Formal concept lattice-based facet search method and system
US10764299B2 (en) * 2017-06-29 2020-09-01 Microsoft Technology Licensing, Llc Access control manager
WO2019005098A1 (en) * 2017-06-30 2019-01-03 Go Logic Decision Time, Llc Methods and systems of assertional projective simulation
US10242390B2 (en) 2017-07-31 2019-03-26 Bank Of America Corporation Digital data processing system for controlling automated exchange zone systems
US10541939B2 (en) 2017-08-15 2020-01-21 Google Llc Systems and methods for provision of a guaranteed batch
CN107545047B (en) * 2017-08-17 2019-07-19 平安科技(深圳)有限公司 The querying method and terminal device of user right data
US10459958B2 (en) 2017-08-29 2019-10-29 Bank Of America Corporation Automated response system using smart data
US10621578B2 (en) 2017-08-29 2020-04-14 Bank Of America Corporation Transferring data using a smart reconciliation system
CN107590372A (en) * 2017-09-06 2018-01-16 叶进蓉 Touch-screen encrypts unlocking method and device
US10733196B2 (en) * 2017-09-18 2020-08-04 Stephen Barry Glickman Method, apparatus, and computer readable medium for modeling relationships between query responses in a data set
US10445429B2 (en) 2017-09-21 2019-10-15 Apple Inc. Natural language understanding using vocabularies with compressed serialized tries
US11093518B1 (en) 2017-09-23 2021-08-17 Splunk Inc. Information technology networked entity monitoring with dynamic metric and threshold selection
US11106442B1 (en) 2017-09-23 2021-08-31 Splunk Inc. Information technology networked entity monitoring with metric selection prior to deployment
US11159397B2 (en) 2017-09-25 2021-10-26 Splunk Inc. Lower-tier application deployment for higher-tier system data monitoring
US10642838B2 (en) * 2017-09-28 2020-05-05 Sap Se Real-time or event-based analysis of process data
CN107659654B (en) * 2017-09-29 2019-08-09 清华大学 The efficient method and device of calling to account of cloudy data integrity damage based on prestige
US10755051B2 (en) * 2017-09-29 2020-08-25 Apple Inc. Rule-based natural language processing
CN107729483B (en) * 2017-10-17 2021-05-11 Oppo广东移动通信有限公司 Classification display method, classification display device, terminal and computer-readable storage medium
US11416563B1 (en) * 2017-10-20 2022-08-16 Amazon Technologies, Inc. Query language for selecting and addressing resources
US10909266B2 (en) * 2017-10-24 2021-02-02 Merck Sharp & Dohme Corp. Adaptive model for database security and processing
US20190130496A1 (en) * 2017-11-01 2019-05-02 Visa International Service Association System, Method, and Computer Program Product for Providing Merchant-Based Social Networks
CN107678892B (en) * 2017-11-07 2021-05-04 黄淮学院 Continuous data protection method based on jump recovery chain
US10839018B2 (en) * 2017-11-15 2020-11-17 International Business Machines Corporation Evaluation of plural expressions corresponding to input data
CN107767083B (en) * 2017-11-16 2019-06-25 哈尔滨理工大学 A kind of grid power transmission quality evaluating method based on division arithmetic judgement
US10691770B2 (en) * 2017-11-20 2020-06-23 Colossio, Inc. Real-time classification of evolving dictionaries
CN107886527A (en) * 2017-11-21 2018-04-06 桂林爱家购股份有限公司 A kind of image processing system and method
CN109840074B (en) * 2017-11-24 2021-02-23 华为技术有限公司 Service generation method, device and network equipment
WO2019104189A1 (en) * 2017-11-27 2019-05-31 Intuition Robotics, Ltd System and method for optimizing resource usage of a robot
US10956401B2 (en) 2017-11-28 2021-03-23 International Business Machines Corporation Checking a technical document of a software program product
US10636424B2 (en) 2017-11-30 2020-04-28 Apple Inc. Multi-turn canned dialog
US11107006B2 (en) * 2017-12-05 2021-08-31 discourse.ai, Inc. Visualization, exploration and shaping conversation data for artificial intelligence-based automated interlocutor training
CN107967415B (en) * 2017-12-11 2021-09-17 北京奇虎科技有限公司 Resource confusion protection method, system and terminal device
US11423052B2 (en) * 2017-12-14 2022-08-23 International Business Machines Corporation User information association with consent-based class rules
US10657145B2 (en) * 2017-12-18 2020-05-19 International Business Machines Corporation Clustering facets on a two-dimensional facet cube for text mining
CN108008997A (en) * 2017-12-22 2018-05-08 北京酷我科技有限公司 A kind of unified method replaced of APP skins
TWI658419B (en) * 2017-12-26 2019-05-01 人因設計所股份有限公司 Sequential exchange method of item matching
US11176486B2 (en) 2017-12-28 2021-11-16 International Business Machines Corporation Building and matching electronic standards profiles using machine learning
US11157980B2 (en) * 2017-12-28 2021-10-26 International Business Machines Corporation Building and matching electronic user profiles using machine learning
US11625628B2 (en) * 2018-01-05 2023-04-11 Daniel Suklja Method of improving processing efficiency decision making within a computer system
US10733982B2 (en) 2018-01-08 2020-08-04 Apple Inc. Multi-directional dialog
CN108280153B (en) * 2018-01-08 2022-01-07 天津科技大学 Intelligent aggregation method for fragmented knowledge
US11663052B2 (en) * 2018-01-08 2023-05-30 Telefonaktiebolaget Lm Ericsson (Publ) Adaptive application assignment to distributed cloud resources
CN108255493B (en) * 2018-01-09 2021-04-23 武汉斗鱼网络科技有限公司 Component publishing and compiling method, storage medium, electronic device and system
CN108154317B (en) * 2018-01-25 2021-09-21 福建师范大学 Workflow group scheduling method based on example self-adaptive distribution integration in multi-cloud environment
US10733375B2 (en) 2018-01-31 2020-08-04 Apple Inc. Knowledge-based framework for improving natural language understanding
CN108415763B (en) * 2018-02-11 2020-12-11 中南大学 Distribution method of edge computing system
US10733192B1 (en) * 2018-02-14 2020-08-04 Intuit Inc. Expression evaluation infrastructure
US10726603B1 (en) * 2018-02-28 2020-07-28 Snap Inc. Animated expressive icon
WO2019167604A1 (en) * 2018-03-02 2019-09-06 住友電気工業株式会社 On-vehicle control device, control system, control method, and control program
US10789959B2 (en) 2018-03-02 2020-09-29 Apple Inc. Training speaker recognition models for digital assistants
JP7155546B2 (en) * 2018-03-05 2022-10-19 富士フイルムビジネスイノベーション株式会社 Information processing device, information processing method, and information processing program
CN108537055B (en) * 2018-03-06 2022-04-05 南京邮电大学 Privacy budget allocation and data release method and system for data query privacy protection
US10592604B2 (en) 2018-03-12 2020-03-17 Apple Inc. Inverse text normalization for automatic speech recognition
US11150632B2 (en) * 2018-03-16 2021-10-19 Yokogawa Electric Corporation System and method for field device management using class parameter set
US10818288B2 (en) 2018-03-26 2020-10-27 Apple Inc. Natural assistant interaction
US10909331B2 (en) 2018-03-30 2021-02-02 Apple Inc. Implicit identification of translation payload with neural machine translation
CN108537866B (en) * 2018-04-11 2022-04-29 北京知道创宇信息技术股份有限公司 Data processing method and device and readable storage medium
US11145294B2 (en) 2018-05-07 2021-10-12 Apple Inc. Intelligent automated assistant for delivering content from user experiences
US10841340B2 (en) * 2018-05-07 2020-11-17 Unisys Corporation Custom node and profile classifications for enterprise security management tool
US11200893B2 (en) * 2018-05-07 2021-12-14 Google Llc Multi-modal interaction between users, automated assistants, and other computing services
US11412003B1 (en) * 2018-05-07 2022-08-09 Amrock, Llc Resource protection and verification with bidirectional notification architecture
JP7203865B2 (en) 2018-05-07 2023-01-13 グーグル エルエルシー Multimodal interaction between users, automated assistants, and other computing services
US10928918B2 (en) 2018-05-07 2021-02-23 Apple Inc. Raise to speak
US11347801B2 (en) * 2018-05-07 2022-05-31 Google Llc Multi-modal interaction between users, automated assistants, and other computing services
CN108364246A (en) * 2018-05-10 2018-08-03 东华大学 A kind of Student Information Management System
US10984780B2 (en) 2018-05-21 2021-04-20 Apple Inc. Global semantic word embeddings using bi-directional recurrent neural networks
US10657712B2 (en) 2018-05-25 2020-05-19 Lowe's Companies, Inc. System and techniques for automated mesh retopology
DK201870355A1 (en) 2018-06-01 2019-12-16 Apple Inc. Virtual assistant operation in multi-device environments
US10892996B2 (en) 2018-06-01 2021-01-12 Apple Inc. Variable latency device coordination
DK179822B1 (en) 2018-06-01 2019-07-12 Apple Inc. Voice interaction at a primary device to access call functionality of a companion device
DK180639B1 (en) 2018-06-01 2021-11-04 Apple Inc DISABILITY OF ATTENTION-ATTENTIVE VIRTUAL ASSISTANT
US11386266B2 (en) 2018-06-01 2022-07-12 Apple Inc. Text correction
US11076039B2 (en) 2018-06-03 2021-07-27 Apple Inc. Accelerated task performance
US10884839B2 (en) 2018-06-07 2021-01-05 Bank Of America Corporation Processing system for performing predictive error resolution and dynamic system configuration control
US10838798B2 (en) 2018-06-07 2020-11-17 Bank Of America Corporation Processing system for performing predictive error resolution and dynamic system configuration control
US10817823B2 (en) * 2018-06-20 2020-10-27 Wipro Limited Method and device for generating data services from heterogeneous systems
US11483313B2 (en) * 2018-06-28 2022-10-25 Intel Corporation Technologies for updating an access control list table without causing disruption
US20200027064A1 (en) * 2018-07-20 2020-01-23 Microsoft Technology Licensing, Llc Task execution based on activity clusters
US11210354B1 (en) * 2018-07-26 2021-12-28 Coupa Software Incorporated Intelligent, adaptive electronic procurement systems
CN109214883A (en) * 2018-07-27 2019-01-15 阿里巴巴集团控股有限公司 Service lease method, apparatus, system and electronic equipment based on block chain
WO2020027857A1 (en) * 2018-08-01 2020-02-06 Centurylink Intellectual Property Llc Machine learning for quality of experience optimization
US11386295B2 (en) 2018-08-03 2022-07-12 Cerebri AI Inc. Privacy and proprietary-information preserving collaborative multi-party machine learning
US10479356B1 (en) 2018-08-17 2019-11-19 Lyft, Inc. Road segment similarity determination
WO2020049367A1 (en) * 2018-09-05 2020-03-12 Chitti Babu K An interactive mathematical operation system and a method to operate the same
CN109241038A (en) * 2018-09-12 2019-01-18 上海外高桥造船有限公司 Sounding table based on NAPA generates system
CN108876270B (en) * 2018-09-19 2022-08-12 惠龙易通国际物流股份有限公司 Automatic goods source auditing system and method
WO2020061087A1 (en) * 2018-09-20 2020-03-26 Ocelot Laboratories Llc Method and device for attenuation of co-user interactions in simulated reality (sr) space
US11010561B2 (en) 2018-09-27 2021-05-18 Apple Inc. Sentiment prediction from textual data
US11170166B2 (en) 2018-09-28 2021-11-09 Apple Inc. Neural typographical error modeling via generative adversarial networks
US10839159B2 (en) 2018-09-28 2020-11-17 Apple Inc. Named entity normalization in a spoken dialog system
US11462215B2 (en) 2018-09-28 2022-10-04 Apple Inc. Multi-modal inputs for voice commands
US11556846B2 (en) 2018-10-03 2023-01-17 Cerebri AI Inc. Collaborative multi-parties/multi-sources machine learning for affinity assessment, performance scoring, and recommendation making
US11086914B2 (en) * 2018-10-08 2021-08-10 International Business Machines Corporation Archiving of topmost ranked answers of a cognitive search
US11362889B2 (en) * 2018-10-15 2022-06-14 Cdw Llc System and method for automated information technology services management
TWI683223B (en) * 2018-10-16 2020-01-21 宏碁股份有限公司 Method and device for filtering data
US11475898B2 (en) 2018-10-26 2022-10-18 Apple Inc. Low-latency multi-speaker speech recognition
BR112021008213A2 (en) * 2018-10-30 2021-08-03 AMI Holdings Limited computer-implemented communications by social media application
US11012387B2 (en) 2018-10-30 2021-05-18 AMI Holdings Limited Apparatus and method for matching individuals during an ephemeral time period based upon voting and matching criteria
US11375656B2 (en) 2018-11-06 2022-07-05 Droneseed Co. Remote drone configuration systems and methods
CN109769328B (en) * 2018-11-13 2020-06-23 大峡谷照明系统(苏州)股份有限公司 Method for inquiring state information of lamp and application of method in light control system
US11328329B1 (en) * 2018-11-16 2022-05-10 Level 3 Communications, Llc Telecommunications infrastructure system and method
CN109688107B (en) * 2018-11-20 2021-11-09 西安电子科技大学 Cloud data safety positioning method based on integrity audit and communication time delay
CN109542969B (en) * 2018-11-23 2023-02-07 国网电力科学研究院武汉南瑞有限责任公司 Text transformer test data structuring system and method
TWI665564B (en) * 2018-11-28 2019-07-11 財團法人資訊工業策進會 Machine tool equipment operation efficienty scoring apparatus and method
CN111527506B (en) * 2018-12-03 2023-09-29 戴斯数字有限责任公司 Data interaction platform utilizing dynamic relationship cognition
US11176271B1 (en) 2018-12-04 2021-11-16 Eightfold AI Inc. System, method, and computer program for enabling a candidate to anonymously apply for a job
WO2021141567A1 (en) 2020-01-06 2021-07-15 Eightfold AI Inc. System, method, and computer program for using machine learning to calibrate job description based on diversity criteria
US11030583B1 (en) 2018-12-04 2021-06-08 Eightfold AI Inc. System, method, and computer program for automatically removing data from candidate profiles that may influence bias
CN110008977B (en) * 2018-12-05 2023-08-11 创新先进技术有限公司 Clustering model construction method and device
US11120109B2 (en) 2018-12-05 2021-09-14 Bank Of America Corporation Processing authentication requests to secured information systems based on machine-learned event profiles
US11036838B2 (en) 2018-12-05 2021-06-15 Bank Of America Corporation Processing authentication requests to secured information systems using machine-learned user-account behavior profiles
US11113370B2 (en) 2018-12-05 2021-09-07 Bank Of America Corporation Processing authentication requests to secured information systems using machine-learned user-account behavior profiles
US11048793B2 (en) 2018-12-05 2021-06-29 Bank Of America Corporation Dynamically generating activity prompts to build and refine machine learning authentication models
US11176230B2 (en) 2018-12-05 2021-11-16 Bank Of America Corporation Processing authentication requests to secured information systems based on user behavior profiles
US11159510B2 (en) 2018-12-05 2021-10-26 Bank Of America Corporation Utilizing federated user identifiers to enable secure information sharing
CN109685136A (en) * 2018-12-21 2019-04-26 云南电网有限责任公司电力科学研究院 A kind of high-pressure heater status data analysis method
CN109829192B (en) * 2018-12-26 2023-10-17 合芯科技(苏州)有限公司 Reference model construction method and device for processor computing unit
CN109753501A (en) * 2018-12-27 2019-05-14 广州市玄武无线科技股份有限公司 A kind of data display method of off-line state, device, equipment and storage medium
US11439346B2 (en) 2019-01-03 2022-09-13 Jacob T. Boyle Robotic device for assisting individuals with a mental illness
US11638059B2 (en) 2019-01-04 2023-04-25 Apple Inc. Content playback on multiple devices
US11093438B2 (en) 2019-01-07 2021-08-17 International Business Machines Corporation Pipelining multi-directional reduction
CN109739667B (en) * 2019-01-10 2021-04-02 广州方硅信息技术有限公司 Message consumption method, device and equipment
CN109885693B (en) * 2019-01-11 2021-08-03 武汉大学 Method and system for rapid knowledge comparison based on knowledge graph
CA3126789A1 (en) * 2019-01-15 2020-07-23 Teejlab Inc. Data management system for web based data services
CN111461855B (en) * 2019-01-18 2023-07-28 同济大学 Credit card fraud detection method and system based on undersampling, medium and equipment
CN109918430B (en) * 2019-01-22 2022-09-23 中国人民解放军战略支援部队信息工程大学 5G user data disassociation storage system and access method
US11461985B2 (en) * 2019-01-30 2022-10-04 Mosaic, Ltd Methods and systems for rendering and modifying three-dimensional models for interior design
US10565365B1 (en) * 2019-02-21 2020-02-18 Capital One Services, Llc Systems and methods for data access control using narrative authentication questions
US11695777B2 (en) * 2019-02-26 2023-07-04 Vmware, Inc. Hybrid access control model in computer systems
US11487586B2 (en) * 2019-02-28 2022-11-01 International Business Machines Corporation Time-based element management in a computer system using temporal node trees
US11133993B2 (en) * 2019-02-28 2021-09-28 At&T Intellectual Property I, L.P. Augmented/mixed reality virtual venue pipeline optimization
US11348573B2 (en) 2019-03-18 2022-05-31 Apple Inc. Multimodality in digital assistant systems
TWI772627B (en) * 2019-03-19 2022-08-01 財團法人工業技術研究院 Person re-identification method, person re-identification system and image screening method
US11943285B2 (en) * 2019-03-22 2024-03-26 International Business Machines Corporation Metering computing resources in cloud computing environments
US20200320449A1 (en) * 2019-04-04 2020-10-08 Rylti, LLC Methods and Systems for Certification, Analysis, and Valuation of Music Catalogs
US20200322664A1 (en) * 2019-04-05 2020-10-08 Grass Valley Canada System and method for ai driven orchestration automation of live production & channel playout
US11397731B2 (en) * 2019-04-07 2022-07-26 B. G. Negev Technologies And Applications Ltd., At Ben-Gurion University Method and system for interactive keyword optimization for opaque search engines
US11654635B2 (en) 2019-04-18 2023-05-23 The Research Foundation For Suny Enhanced non-destructive testing in directed energy material processing
CN110188071B (en) * 2019-04-19 2021-11-02 北京奇艺世纪科技有限公司 Data processing method and device, electronic equipment and computer readable medium
CN110097119A (en) * 2019-04-30 2019-08-06 西安理工大学 Difference secret protection support vector machine classifier algorithm based on dual variable disturbance
US11697963B2 (en) * 2019-05-01 2023-07-11 Oldcastle BuildingEnvelope Inc. Insulating panel assembly
US11307752B2 (en) 2019-05-06 2022-04-19 Apple Inc. User configurable task triggers
US11475884B2 (en) 2019-05-06 2022-10-18 Apple Inc. Reducing digital assistant latency when a language is incorrectly determined
DK201970509A1 (en) 2019-05-06 2021-01-15 Apple Inc Spoken notifications
US11423908B2 (en) 2019-05-06 2022-08-23 Apple Inc. Interpreting spoken requests
US11140099B2 (en) 2019-05-21 2021-10-05 Apple Inc. Providing message response suggestions
US11163956B1 (en) 2019-05-23 2021-11-02 Intuit Inc. System and method for recognizing domain specific named entities using domain specific word embeddings
CN110162404B (en) * 2019-05-28 2023-07-14 深信服科技股份有限公司 Method, system, equipment and computer medium for distributing resources of secure resource pool
US11496600B2 (en) 2019-05-31 2022-11-08 Apple Inc. Remote execution of machine-learned models
DK201970510A1 (en) 2019-05-31 2021-02-11 Apple Inc Voice identification in digital assistant systems
US11289073B2 (en) 2019-05-31 2022-03-29 Apple Inc. Device text to speech
DK180129B1 (en) 2019-05-31 2020-06-02 Apple Inc. User activity shortcut suggestions
US11468890B2 (en) 2019-06-01 2022-10-11 Apple Inc. Methods and user interfaces for voice-based control of electronic devices
US11360641B2 (en) 2019-06-01 2022-06-14 Apple Inc. Increasing the relevance of new available information
US11928557B2 (en) 2019-06-13 2024-03-12 Lyft, Inc. Systems and methods for routing vehicles to capture and evaluate targeted scenarios
US11550937B2 (en) * 2019-06-13 2023-01-10 Fujitsu Limited Privacy trustworthiness based API access
US11443263B2 (en) * 2019-06-18 2022-09-13 Heyhq, Inc. Organizational risk management subscription service
CN110363469B (en) * 2019-06-18 2022-06-14 北京你财富计算机科技有限公司 Method and device for automatically filling movable products in distribution platform and electronic equipment
CN110232157B (en) * 2019-06-18 2024-02-02 绍兴文理学院 Content-based privacy protection book recommendation method and system
US11258800B2 (en) 2019-06-28 2022-02-22 Slack Technologies, Llc Managing admin controlled access of external resources to group-based communication interfaces via a group-based communication system
US10970224B2 (en) 2019-06-28 2021-04-06 International Business Machines Corporation Operational context subspaces
US11074195B2 (en) 2019-06-28 2021-07-27 International Business Machines Corporation Access to dynamic address translation across multiple spaces for operational context subspaces
US11176056B2 (en) 2019-06-28 2021-11-16 International Business Machines Corporation Private space control within a common address space
US11449475B2 (en) 2019-06-28 2022-09-20 Lyft, Inc. Approaches for encoding environmental information
US11157007B2 (en) * 2019-06-28 2021-10-26 Lyft, Inc. Approaches for encoding environmental information
US10891238B1 (en) 2019-06-28 2021-01-12 International Business Machines Corporation Dynamically joining and splitting dynamic address translation (DAT) tables based on operational context
CN110287434B (en) * 2019-07-02 2022-02-25 郑州悉知信息科技股份有限公司 Website processing method and device and storage medium
CN110414087B (en) * 2019-07-10 2023-01-24 北京华安中泰检测技术有限公司 Electronic product service life evaluation method under multi-stress coupling effect
EP3770769A1 (en) * 2019-07-23 2021-01-27 Siemens Aktiengesellschaft Method for querying or processing a complete file by means of a query language and device for managing said method
US11138978B2 (en) * 2019-07-24 2021-10-05 International Business Machines Corporation Topic mining based on interactionally defined activity sequences
US11558425B2 (en) * 2019-07-31 2023-01-17 EMC IP Holding Company LLC Dynamic access controls using verifiable claims
CN110457302B (en) * 2019-07-31 2022-04-29 河南开合软件技术有限公司 Intelligent structured data cleaning method
US20210042713A1 (en) * 2019-08-05 2021-02-11 Bank Of America Corporation Intelligent attribute spatial scanning system
US11356477B2 (en) * 2019-08-05 2022-06-07 Twilio Inc. Verifying incoming communications
CN110610527B (en) * 2019-08-15 2023-09-22 苏州瑞派宁科技有限公司 SUV computing method, device, equipment, system and computer storage medium
WO2021035193A1 (en) * 2019-08-22 2021-02-25 Google Llc Active learning via a sample consistency assessment
JP7326501B2 (en) * 2019-08-22 2023-08-15 グーグル エルエルシー Reduced propagation latency
US11386400B2 (en) * 2019-09-03 2022-07-12 Citrix Systems, Inc. Unified event/task creation from auto generated enterprise communication channels and notifications
CN110535756A (en) * 2019-09-04 2019-12-03 黄淮学院 A kind of group communication method based on geographical location information
CN110716999B (en) * 2019-09-05 2021-10-22 武汉大学 POI positioning method based on position description containing qualitative position and quantitative distance
US11409962B2 (en) * 2019-09-17 2022-08-09 Eugenie Technologies Private Limited System and method for automated insight curation and alerting
WO2021056255A1 (en) 2019-09-25 2021-04-01 Apple Inc. Text detection using global geometry estimators
CN110727384B (en) * 2019-09-26 2022-04-22 北京金山安全软件有限公司 Unread message quantity statistical method and device and electronic equipment
US11788846B2 (en) 2019-09-30 2023-10-17 Lyft, Inc. Mapping and determining scenarios for geographic regions
CN110839014B (en) * 2019-10-12 2022-03-01 平安科技(深圳)有限公司 Authentication method, authentication device, computer equipment and readable storage medium
CN112667434A (en) * 2019-10-16 2021-04-16 伊姆西Ip控股有限责任公司 Method, apparatus and computer program product for recovering data
US11442944B2 (en) 2019-10-18 2022-09-13 Thinkspan, LLC Algorithmic suggestions based on a universal data scaffold
WO2021077038A1 (en) 2019-10-18 2021-04-22 Taylor Brian Samuel Scalable scaffolding and bundled data
CN110738982B (en) * 2019-10-22 2022-01-28 珠海格力电器股份有限公司 Request processing method and device and electronic equipment
US11816900B2 (en) 2019-10-23 2023-11-14 Lyft, Inc. Approaches for encoding environmental information
CN110569329B (en) * 2019-10-28 2022-08-02 深圳市商汤科技有限公司 Data processing method and device, electronic equipment and storage medium
CN110765159B (en) * 2019-11-01 2022-08-12 上海达梦数据库有限公司 Object analysis method, device, storage medium and equipment
US11831670B1 (en) 2019-11-18 2023-11-28 Tanium Inc. System and method for prioritizing distributed system risk remediations
US11290390B2 (en) 2019-11-20 2022-03-29 Oracle International Corporation Methods, systems, and computer readable media for lockless communications network resource quota sharing
CN111079987A (en) * 2019-11-28 2020-04-28 电子科技大学 Semiconductor workshop production scheduling method based on genetic algorithm
CN110768269B (en) * 2019-12-03 2021-04-09 西安西电电力系统有限公司 Static synchronous compensation device and control method thereof
US11531939B1 (en) 2019-12-23 2022-12-20 Workday, Inc. Shift design and assignment system
US11763220B1 (en) 2019-12-23 2023-09-19 Workday, Inc. Shift design and assignment system with efficient incremental solution
US11948106B1 (en) 2019-12-23 2024-04-02 Workday, Inc. Shift design and assignment system with flexible modeling of constraint and cost function
US11356317B2 (en) * 2019-12-24 2022-06-07 Vmware, Inc. Alarm prioritization in a 5G telco network
US11914807B2 (en) * 2019-12-30 2024-02-27 Shanghai Harvest Intelligence Technology Co., Ltd Method and device for biometric recognition
CN111506416B (en) * 2019-12-31 2023-09-12 远景智能国际私人投资有限公司 Computing method, scheduling method, related device and medium of edge gateway
CN111182239B (en) * 2020-01-12 2021-07-06 苏州浪潮智能科技有限公司 AI video processing method and device
CN111240882B (en) * 2020-01-16 2020-11-20 深圳开源互联网安全技术有限公司 Method and system for detecting abnormal state
CN111831681B (en) * 2020-01-22 2022-03-25 浙江连信科技有限公司 Intelligent terminal-based personnel discrimination method and device
US11803510B2 (en) 2020-02-10 2023-10-31 International Business Machines Corporation Labeling software applications running on nodes of a data center
US11783128B2 (en) 2020-02-19 2023-10-10 Intuit Inc. Financial document text conversion to computer readable operations
TWI745878B (en) * 2020-03-05 2021-11-11 宏碁股份有限公司 Chat robot system and chat robot model training method
CN111382309B (en) * 2020-03-10 2023-04-18 深圳大学 Short video recommendation method based on graph model, intelligent terminal and storage medium
CN111461558B (en) * 2020-04-04 2022-04-22 中国人民解放军海军工程大学 Key data safety destruction evaluation method
US11568136B2 (en) * 2020-04-15 2023-01-31 Forcepoint Llc Automatically constructing lexicons from unlabeled datasets
US10713016B1 (en) * 2020-05-04 2020-07-14 Loyalty Juggernaut, Inc Method of implementing rules on visual language using visual blocks
US11360748B2 (en) * 2020-05-04 2022-06-14 Loyalty Juggernaut, Inc. System and method of collectively tracking a behavior of a member across one or more dimensions
CN111711986B (en) * 2020-05-06 2022-06-07 哈尔滨工业大学 UC-UDN proportional fair resource allocation method in 5G communication system
WO2021226184A1 (en) 2020-05-06 2021-11-11 Morgan Stanley Services Group Inc. Automated knowledge base
US11061543B1 (en) 2020-05-11 2021-07-13 Apple Inc. Providing relevant data items based on context
US11043220B1 (en) 2020-05-11 2021-06-22 Apple Inc. Digital assistant hardware abstraction
US11755276B2 (en) 2020-05-12 2023-09-12 Apple Inc. Reducing description length based on confidence
CN111737383B (en) * 2020-05-21 2021-11-23 百度在线网络技术(北京)有限公司 Method for extracting spatial relation of geographic position points and method and device for training extraction model
CN111737622B (en) * 2020-06-18 2023-07-04 上海英方软件股份有限公司 Method and device for subscribing market information stream
EP4173232A1 (en) * 2020-06-29 2023-05-03 Illumina, Inc. Temporary cloud provider credentials via secure discovery framework
US11194966B1 (en) * 2020-06-30 2021-12-07 International Business Machines Corporation Management of concepts and intents in conversational systems
US11490204B2 (en) 2020-07-20 2022-11-01 Apple Inc. Multi-device audio adjustment coordination
US11438683B2 (en) 2020-07-21 2022-09-06 Apple Inc. User identification using headphones
CN113268964B (en) * 2020-07-23 2022-01-18 腾讯科技(深圳)有限公司 Table editing method, device, equipment and storage medium
US11563764B1 (en) 2020-08-24 2023-01-24 Tanium Inc. Risk scoring based on compliance verification test results in a local network
CN114153980A (en) * 2020-09-07 2022-03-08 中兴通讯股份有限公司 Knowledge graph construction method and device, inspection method and storage medium
USD958258S1 (en) * 2020-10-06 2022-07-19 Ec Innovation Inc. Balloon base
EP3985528A1 (en) * 2020-10-16 2022-04-20 ABB Schweiz AG Negotiation of information contracts between information providers and consumers
CN112416754B (en) * 2020-11-02 2021-09-03 中关村科学城城市大脑股份有限公司 Model evaluation method, terminal, system and storage medium
CN112329387B (en) * 2020-11-03 2024-03-05 新奥数能科技有限公司 Formula template configuration method and device
US11640565B1 (en) 2020-11-11 2023-05-02 Wells Fargo Bank, N.A. Systems and methods for relationship mapping
US11392573B1 (en) 2020-11-11 2022-07-19 Wells Fargo Bank, N.A. Systems and methods for generating and maintaining data objects
CN112149261B (en) * 2020-11-24 2021-05-11 上海索辰信息科技股份有限公司 Rotating mechanical structure strength simulation system and method based on direct analog calculation
US20220174534A1 (en) * 2020-11-27 2022-06-02 At&T Intellectual Property I, L.P. Automatic adjustment of throughput rate to optimize wireless device battery performance
US11847597B2 (en) * 2020-11-29 2023-12-19 Performetriks Llc Computer network with a performance engineering maturity model system
US20220174076A1 (en) * 2020-11-30 2022-06-02 Microsoft Technology Licensing, Llc Methods and systems for recognizing video stream hijacking on edge devices
US20220171773A1 (en) * 2020-12-01 2022-06-02 International Business Machines Corporation Optimizing expansion of user query input in natural language processing applications
CN112416599B (en) * 2020-12-03 2023-03-24 腾讯科技(深圳)有限公司 Resource scheduling method, device, equipment and computer readable storage medium
CN112751749B (en) * 2020-12-30 2022-10-11 上海掌门科技有限公司 Method and equipment for presenting information in audio and video calling process
US11676072B1 (en) 2021-01-29 2023-06-13 Splunk Inc. Interface for incorporating user feedback into training of clustering model
US20220245552A1 (en) * 2021-02-03 2022-08-04 Dynatrace Llc Optimizing Cloud-Based IT-Systems Towards Business Objectives: Automatic Topology-Based Analysis To Determine Impact Of IT-Systems On Business Metrics
CN112883078B (en) * 2021-02-07 2022-11-15 江西科技学院 Track dynamic inspection historical data matching method based on DTW and least square estimation
US20220269656A1 (en) * 2021-02-25 2022-08-25 HCL America Inc. Resource unit management database and system for storing and managing information about information technology resources
US11405225B1 (en) * 2021-03-17 2022-08-02 International Business Machines Corporation Collaboration platform recommendation tool
US11720521B2 (en) 2021-03-29 2023-08-08 Alibaba Singapore Holding Private Limited Topologies and algorithms for multi-processing unit interconnected accelerator systems
CN112737896B (en) * 2021-04-01 2021-06-25 北京视界云天科技有限公司 Bandwidth data checking method, device, medium and electronic equipment
US11763228B2 (en) * 2021-04-06 2023-09-19 Nice Ltd. Systems and methods for analyzing and connecting automation sequences
CA3217347A1 (en) * 2021-04-23 2022-10-27 Battelle Memorial Institute Causal relational artificial intelligence and risk framework for manufacturing applications
DE102021002354A1 (en) 2021-04-28 2022-11-10 Universität Stuttgart, Körperschaft Des Öffentlichen Rechts Resource-based concept for operational planning of distributed space systems
AU2022202863A1 (en) * 2021-04-30 2022-11-17 People Center, Inc. Improved Management of Computing Devices Via Reference to Linked Employee Records
CN113238533B (en) * 2021-05-12 2022-05-13 广东美房智高机器人有限公司 System and method for dynamically scheduling and issuing job tasks of mobile robot
CN113361232B (en) * 2021-05-14 2023-11-28 武汉大学 Cross-border service target fusion conflict detection method and device
US11514042B1 (en) * 2021-06-03 2022-11-29 Sap Se Managing multiple cache specifications within a database environment
US20220391750A1 (en) * 2021-06-03 2022-12-08 Truata Limited System for harnessing knowledge and expertise to improve machine learning
CN113377775B (en) * 2021-06-21 2024-02-02 特赞(上海)信息科技有限公司 Information processing method and device
CN113448314A (en) * 2021-06-28 2021-09-28 重庆长安汽车股份有限公司 Hardware resource-based whole vehicle function service abstraction system and method
US20230015789A1 (en) * 2021-07-08 2023-01-19 Vmware, Inc. Aggregation of user authorizations from different providers in a hybrid cloud environment
US20230015697A1 (en) * 2021-07-13 2023-01-19 Citrix Systems, Inc. Application programming interface (api) authorization
CN113254026B (en) * 2021-07-19 2021-10-01 国网汇通金财(北京)信息科技有限公司 Low code development method and device
CN113535942B (en) * 2021-07-21 2022-08-19 北京海泰方圆科技股份有限公司 Text abstract generating method, device, equipment and medium
CN113703886B (en) * 2021-07-21 2023-06-20 青岛海尔科技有限公司 User system behavior monitoring method, system, electronic equipment and storage medium
CN113298911B (en) * 2021-07-26 2021-10-08 湖南高至科技有限公司 Graphical concept modeling method based on lambda rule
US20230094856A1 (en) * 2021-09-20 2023-03-30 Normalyze, Inc. Compact cloud access network based on role-to-resource detection with resource state change tracking and provenance
US11575696B1 (en) 2021-09-20 2023-02-07 Normalyze, Inc. Cloud data attack detection based on cloud security posture and resource network path tracing
US20230129824A1 (en) * 2021-10-21 2023-04-27 Jpmorgan Chase Bank, N.A. Systems and methods for cloud federated token just in time authorization
CN113824193B (en) * 2021-10-27 2023-05-23 四川大学 Impedance matching method, apparatus, reinforcement learning controller, and computer-readable storage medium
US11954159B2 (en) * 2021-11-09 2024-04-09 Adp, Inc. System and method for using graph theory to rank characteristics
CN114139039B (en) * 2021-11-30 2022-08-09 百度在线网络技术(北京)有限公司 Service stability determination method, device, equipment and storage medium
CN114115284B (en) * 2021-12-02 2022-12-06 北京理工大学 Unknown maze traversal method based on detection and following of nearest and unaccessed gaps to target
US20230259505A1 (en) * 2022-01-26 2023-08-17 Oracle International Corporation Future transaction processing
WO2023148518A1 (en) * 2022-02-02 2023-08-10 Featurespace Limited Storing and searching for data in data stores
US11803599B2 (en) * 2022-03-15 2023-10-31 My Job Matcher, Inc. Apparatus and method for attribute data table matching
CN114820225B (en) 2022-06-28 2022-09-13 成都秦川物联网科技股份有限公司 Industrial Internet of things based on keyword recognition and manufacturing problem processing and control method
CN115174618B (en) * 2022-06-30 2023-05-26 重庆长安汽车股份有限公司 Internet of vehicles module, internet of vehicles access method, equipment and medium
CN114936329B (en) * 2022-07-22 2022-11-04 江西水利职业学院(江西省水利水电学校、江西省灌溉排水发展中心、江西省水利工程技师学院) Social contact management method and system based on campus library
CN115237506B (en) * 2022-09-21 2022-12-09 暨南大学 Reliability-driven hierarchical task unloading method and device in CPS (control performance Standard) system
CN115270738B (en) * 2022-09-30 2023-02-03 北京澜舟科技有限公司 Research and report generation method, system and computer storage medium
CN115455383B (en) * 2022-11-14 2023-03-24 北京奕之宣科技有限公司 Method, device and equipment for processing watermark information of database
CN116185614B (en) * 2023-01-09 2024-04-05 明阳产业技术研究院(沈阳)有限公司 Multi-server load balancing method, system, medium and equipment
CN115827621B (en) * 2023-02-17 2023-05-16 河北雄安睿天科技有限公司 Water affair data management system based on cloud computing and data analysis
US11949638B1 (en) 2023-03-04 2024-04-02 Unanimous A. I., Inc. Methods and systems for hyperchat conversations among large networked populations with collective intelligence amplification
CN116414430B (en) * 2023-04-17 2023-09-26 北京计算机技术及应用研究所 Quantization method based on rule engine Drools
CN116679889B (en) * 2023-07-31 2023-11-03 苏州浪潮智能科技有限公司 Method and device for determining RAID equipment configuration information and storage medium
CN116720006B (en) * 2023-08-10 2023-11-03 数据空间研究院 Fair recommendation method, device and medium based on limited user sensitivity attribute
CN116775744B (en) * 2023-08-17 2023-11-07 中国电子科技集团公司第十五研究所 Multi-source data fusion method and device and electronic equipment
CN117667751B (en) * 2024-02-01 2024-04-19 道普信息技术有限公司 Automatic testing method for low-coupling WEB service

Family Cites Families (172)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2967012B2 (en) 1993-01-07 1999-10-25 富士電機株式会社 Personal recognition device
US8505108B2 (en) 1993-11-18 2013-08-06 Digimarc Corporation Authentication using a digital watermark
US5794050A (en) 1995-01-04 1998-08-11 Intelligent Text Processing, Inc. Natural language understanding system
US5892900A (en) 1996-08-30 1999-04-06 Intertrust Technologies Corp. Systems and methods for secure transaction management and electronic rights protection
US20030191719A1 (en) 1995-02-13 2003-10-09 Intertrust Technologies Corp. Systems and methods for secure transaction management and electronic rights protection
US6948070B1 (en) 1995-02-13 2005-09-20 Intertrust Technologies Corporation Systems and methods for secure transaction management and electronic rights protection
DE69638018D1 (en) 1995-02-13 2009-10-15 Intertrust Tech Corp Systems and procedures for managing secure transactions and protecting electronic rights
JP3738787B2 (en) * 1995-10-19 2006-01-25 富士ゼロックス株式会社 Resource management apparatus and resource management method
US5893057A (en) 1995-10-24 1999-04-06 Ricoh Company Ltd. Voice-based verification and identification methods and systems
US5828751A (en) 1996-04-08 1998-10-27 Walker Asset Management Limited Partnership Method and apparatus for secure measurement certification
US5933502A (en) 1996-12-20 1999-08-03 Intel Corporation Method and apparatus for enhancing the integrity of visual authentication
AUPO710597A0 (en) 1997-06-02 1997-06-26 Knowledge Horizons Pty. Ltd. Methods and systems for knowledge management
US6523022B1 (en) * 1997-06-09 2003-02-18 Allen Hobbs Method and apparatus for selectively augmenting retrieved information from a network resource
US6112181A (en) 1997-11-06 2000-08-29 Intertrust Technologies Corporation Systems and methods for matching, selecting, narrowcasting, and/or classifying based on rights management and/or other information
US6353824B1 (en) 1997-11-18 2002-03-05 Apple Computer, Inc. Method for dynamic presentation of the contents topically rich capsule overviews corresponding to the plurality of documents, resolving co-referentiality in document segments
US6607136B1 (en) 1998-09-16 2003-08-19 Beepcard Inc. Physical presence digital authentication system
US20020056043A1 (en) 1999-01-18 2002-05-09 Sensar, Inc. Method and apparatus for securely transmitting and authenticating biometric data over a network
CA2271178A1 (en) 1999-05-06 1999-07-06 Connotech Experts-Conseils Inc. Server-side public key cryptography apparatus with private key protection and isolation from public networks
JP2001195145A (en) 2000-01-07 2001-07-19 Seiko Instruments Inc Information processor, individual authentication method and computer readable recording medium recording program to make computer execute the method
US20020087496A1 (en) 2000-04-05 2002-07-04 Stirpe Paul A. System, method and applications for knowledge commerce
US7082463B1 (en) 2000-06-07 2006-07-25 Cisco Technology, Inc. Time-based monitoring of service level agreements
US20020046041A1 (en) 2000-06-23 2002-04-18 Ken Lang Automated reputation/trust service
AU7182701A (en) 2000-07-06 2002-01-21 David Paul Felsher Information record infrastructure, system and method
US6675159B1 (en) 2000-07-27 2004-01-06 Science Applic Int Corp Concept-based search and retrieval system
GB0028278D0 (en) 2000-11-20 2001-01-03 Tao Group Ltd Personal authentication system
US7028035B1 (en) 2000-12-08 2006-04-11 Hewlett-Packard Development Company, L.P. Method and system of typing resources in a distributed system
US7921297B2 (en) 2001-01-10 2011-04-05 Luis Melisendro Ortiz Random biometric authentication utilizing unique biometric signatures
DE10101995A1 (en) 2001-01-18 2002-07-25 Philips Corp Intellectual Pty Electrical or electronic switching arrangement comprises a detector unit and a comparator unit connected to the detector unit to compare the starting voltage with a reference voltage
US20020093529A1 (en) 2001-01-18 2002-07-18 Raja Daoud Method and apparatus to optimize a computing session based on user interaction with a computer
CA2438834C (en) 2001-03-08 2012-05-15 California Institute Of Technology Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking
KR20030094261A (en) * 2001-03-08 2003-12-11 인터내셔널 비지네스 머신즈 코포레이션 System and Method For Personalized Presentation Of Web Pages
US7181017B1 (en) 2001-03-23 2007-02-20 David Felsher System and method for secure three-party communications
TW540235B (en) * 2001-05-10 2003-07-01 Ibm System and method for enhancing broadcast programs with information on the world wide web
US7281043B1 (en) * 2001-05-31 2007-10-09 Cisco Technology, Inc. System for sharing resources among RSVP sessions
EP1402408A1 (en) * 2001-07-04 2004-03-31 Cogisum Intermedia AG Category based, extensible and interactive system for document retrieval
US7526425B2 (en) 2001-08-14 2009-04-28 Evri Inc. Method and system for extending keyword searching to syntactically and semantically annotated data
US7089298B2 (en) 2001-08-20 2006-08-08 Nokia Corporation Naming distribution method for ad hoc networks
US7018412B2 (en) 2001-08-20 2006-03-28 Ebi, L.P. Allograft spinal implant
WO2003038673A2 (en) * 2001-10-31 2003-05-08 Gen-I Limited Information archiving software
NO316480B1 (en) 2001-11-15 2004-01-26 Forinnova As Method and system for textual examination and discovery
US6724689B2 (en) 2002-03-08 2004-04-20 Philip Koenig Personal identification method and apparatus using acoustic resonance analysis of body parts
WO2003077079A2 (en) 2002-03-08 2003-09-18 Enleague Systems, Inc Methods and systems for modeling and using computer resources over a heterogeneous distributed network using semantic ontologies
US7363363B2 (en) 2002-05-17 2008-04-22 Xds, Inc. System and method for provisioning universal stateless digital and computing services
WO2012125726A1 (en) 2011-03-14 2012-09-20 Intelligent Technologies International, Inc. Cargo theft prevention system and method
US6946715B2 (en) * 2003-02-19 2005-09-20 Micron Technology, Inc. CMOS image sensor and method of fabrication
US7543156B2 (en) 2002-06-25 2009-06-02 Resilent, Llc Transaction authentication card
US7333798B2 (en) 2002-08-08 2008-02-19 Value Added Communications, Inc. Telecommunication call management and monitoring system
CN1701343A (en) * 2002-09-20 2005-11-23 德克萨斯大学董事会 Computer program products, systems and methods for information discovery and relational analyses
US20060057550A1 (en) 2002-09-27 2006-03-16 Nozomu Sahashi Remote education system, course attendance check method, and course attendance check program
US7467206B2 (en) 2002-12-23 2008-12-16 Microsoft Corporation Reputation system for web services
US9818136B1 (en) 2003-02-05 2017-11-14 Steven M. Hoffberg System and method for determining contingent relevance
US7587611B2 (en) 2003-05-30 2009-09-08 Privaris, Inc. In-circuit security system and methods for controlling access to and use of sensitive data
US7739602B2 (en) 2003-06-24 2010-06-15 Aol Inc. System and method for community centric resource sharing based on a publishing subscription model
CN101241735B (en) 2003-07-07 2012-07-18 罗威所罗生股份有限公司 Method for replaying encrypted video and audio content
US7313533B2 (en) 2003-07-11 2007-12-25 International Business Machines Corporation Systems and methods for monitoring and controlling business level service level agreements
EP1678869A1 (en) 2003-10-08 2006-07-12 Stephan J. Engberg Method and sytem for establishing a communication using privacy enhancing techniques
JP2005165958A (en) * 2003-12-05 2005-06-23 Ibm Japan Ltd Information retrieval system, information retrieval support system and method therefor, and program
US7543331B2 (en) 2003-12-22 2009-06-02 Sun Microsystems, Inc. Framework for providing a configurable firewall for computing systems
US8010459B2 (en) 2004-01-21 2011-08-30 Google Inc. Methods and systems for rating associated members in a social network
CA2559593C (en) * 2004-03-13 2013-12-31 Cluster Resources, Inc. System and method of co-allocating a reservation spanning different compute resources types
US20050206501A1 (en) 2004-03-16 2005-09-22 Michael Farhat Labor management system and method using a biometric sensing device
JP2005309907A (en) * 2004-04-23 2005-11-04 Hewlett-Packard Development Co Lp Method, device, and program for creating digest of user comment
US8918900B2 (en) 2004-04-26 2014-12-23 Ivi Holdings Ltd. Smart card for passport, electronic passport, and method, system, and apparatus for authenticating person holding smart card or electronic passport
EP1800217A4 (en) * 2004-08-31 2009-06-24 Ibm Architecture for enterprise data integration systems
US8010460B2 (en) 2004-09-02 2011-08-30 Linkedin Corporation Method and system for reputation evaluation of online users in a social networking scheme
US8166296B2 (en) 2004-10-20 2012-04-24 Broadcom Corporation User authentication system
US7433838B2 (en) 2004-11-19 2008-10-07 Microsoft Corporation Realizing legally binding business contracts through service management models
US20060112278A1 (en) 2004-11-19 2006-05-25 Cohen Mark S Method and system for biometric authentication of user feedback
US20060136717A1 (en) 2004-12-20 2006-06-22 Mark Buer System and method for authentication via a proximate device
WO2006101169A1 (en) * 2005-03-23 2006-09-28 Ihc Corp. Authentication system
US7536304B2 (en) 2005-05-27 2009-05-19 Porticus, Inc. Method and system for bio-metric voice print authentication
US7761399B2 (en) 2005-08-19 2010-07-20 Evree Llc Recommendation networks for ranking recommendations using trust rating for user-defined topics and recommendation rating for recommendation sources
US7849501B2 (en) 2005-09-30 2010-12-07 At&T Intellectual Property I, L.P. Methods and systems for using data processing systems in order to authenticate parties
US7673040B2 (en) 2005-10-06 2010-03-02 Microsoft Corporation Monitoring of service provider performance
US8374973B2 (en) 2006-02-16 2013-02-12 Microsoft Corporation Reputation system
US20080040428A1 (en) 2006-04-26 2008-02-14 Xu Wei Method for establishing a social network system based on motif, social status and social attitude
US7603350B1 (en) 2006-05-09 2009-10-13 Google Inc. Search result ranking based on trust
US9318108B2 (en) 2010-01-18 2016-04-19 Apple Inc. Intelligent automated assistant
US20080070697A1 (en) 2006-09-15 2008-03-20 Icebreaker, Inc. Social interaction games and activities
US20080109245A1 (en) 2006-11-03 2008-05-08 Sezwho Inc. Method and system for managing domain specific and viewer specific reputation on online communities
US20080109244A1 (en) 2006-11-03 2008-05-08 Sezwho Inc. Method and system for managing reputation profile on online communities
US8565815B2 (en) 2006-11-16 2013-10-22 Digimarc Corporation Methods and systems responsive to features sensed from imagery or other data
US20080126929A1 (en) 2006-11-29 2008-05-29 Microsoft Corporation Remote ui for smart devices
US8380902B2 (en) 2006-12-05 2013-02-19 Newton Howard Situation understanding and intent-based analysis for dynamic information exchange
US8655939B2 (en) 2007-01-05 2014-02-18 Digital Doors, Inc. Electromagnetic pulse (EMP) hardened information infrastructure with extractor, cloud dispersal, secure storage, content analysis and classification and method therefor
US8674804B2 (en) 2007-03-01 2014-03-18 Deadman Technologies, Llc Control of equipment using remote display
US8362873B2 (en) 2007-03-01 2013-01-29 Deadman Technologies, Llc Control of equipment using remote display
US8706914B2 (en) 2007-04-23 2014-04-22 David D. Duchesneau Computing infrastructure
US8042122B2 (en) 2007-06-27 2011-10-18 Microsoft Corporation Hybrid resource manager
US8838659B2 (en) 2007-10-04 2014-09-16 Amazon Technologies, Inc. Enhanced knowledge repository
US8112791B2 (en) 2007-11-14 2012-02-07 Kiester W Scott Secure launching of browser from privileged process
US8291492B2 (en) 2007-12-12 2012-10-16 Google Inc. Authentication of a contributor of online content
US7734609B2 (en) 2008-01-03 2010-06-08 Firehose, Llc Multi-level reputation based recommendation system and method
CN101981570A (en) * 2008-04-01 2011-02-23 雅虎公司 Open framework for integrating, associating and interacting with content objects
JP5111256B2 (en) 2008-06-23 2013-01-09 株式会社日立製作所 Communication system and server device
US8660321B2 (en) * 2008-11-19 2014-02-25 Nec Corporation Authentication system, apparatus, authentication method, and storage medium with program stored therein
JP5147673B2 (en) 2008-12-18 2013-02-20 株式会社日立製作所 Biometric authentication system and method
US8468355B2 (en) 2008-12-19 2013-06-18 University Of South Carolina Multi-dimensional credentialing using veiled certificates
US8199507B2 (en) 2008-12-19 2012-06-12 Openpeak Inc. Telephony and digital media services device
US8612582B2 (en) * 2008-12-19 2013-12-17 Openpeak Inc. Managed services portals and method of operation of same
CN101772171B (en) * 2009-01-06 2015-07-22 中兴通讯股份有限公司 Group resource allocation method
US8255500B2 (en) 2009-01-09 2012-08-28 Ganart Technologies, Inc. Remotely configurable user device with physical user resources and interface
US9066141B2 (en) * 2009-01-21 2015-06-23 Juniper Networks, Inc. Resource allocation and modification using statistical analysis
DE102009005810A1 (en) 2009-01-22 2010-07-29 Jäger, Hubert, Dr. Device for generating a virtual network user
US8194858B2 (en) 2009-02-19 2012-06-05 Physical Optics Corporation Chaotic cipher system and method for secure communication
WO2010105246A2 (en) 2009-03-12 2010-09-16 Exbiblio B.V. Accessing resources based on capturing information from a rendered document
US9864637B2 (en) 2009-03-18 2018-01-09 Microsoft Technology Licensing, Llc Adaptable software resource managers based on intentions
JP5320561B2 (en) 2009-03-19 2013-10-23 株式会社日立製作所 Terminal system for guaranteeing authenticity, terminal and terminal management server
US8510263B2 (en) * 2009-06-15 2013-08-13 Verisign, Inc. Method and system for auditing transaction data from database operations
US20110083018A1 (en) 2009-10-06 2011-04-07 Validity Sensors, Inc. Secure User Authentication
US20120011358A1 (en) 2009-10-13 2012-01-12 Google Inc. Remote administration and delegation rights in a cloud-based computing device
US8726407B2 (en) 2009-10-16 2014-05-13 Deviceauthority, Inc. Authentication of computing and communications hardware
EP2497055B1 (en) 2009-11-05 2018-07-18 Trusted Logic Secure portable object
US8250213B2 (en) 2009-11-16 2012-08-21 At&T Intellectual Property I, L.P. Methods and apparatus to allocate resources associated with a distributive computing network
US20110126197A1 (en) 2009-11-25 2011-05-26 Novell, Inc. System and method for controlling cloud and virtualized data centers in an intelligent workload management system
CN102782732B (en) 2009-12-18 2017-06-27 Nxp股份有限公司 The protected mode of global platform compatible smartcard
US20110161309A1 (en) 2009-12-29 2011-06-30 Lx1 Technology Limited Method Of Sorting The Result Set Of A Search Engine
US8520842B2 (en) * 2010-01-07 2013-08-27 Microsoft Corporation Maintaining privacy during user profiling
EP2354967A1 (en) 2010-01-29 2011-08-10 British Telecommunications public limited company Semantic textual analysis
WO2011097411A2 (en) 2010-02-03 2011-08-11 Glomantra Inc. Method and system for need fulfillment
EP2559030B1 (en) * 2010-03-19 2017-06-21 Digimarc Corporation Intuitive computing methods and systems
FR2959091B1 (en) * 2010-04-16 2014-06-20 Inst Nat Rech Inf Automat COMPUTER RESOURCE AND INFRASTRUCTURE MANAGEMENT TOOL AND NETWORKS
US9110882B2 (en) 2010-05-14 2015-08-18 Amazon Technologies, Inc. Extracting structured knowledge from unstructured text
US8484474B2 (en) 2010-07-01 2013-07-09 Rockwell Automation Technologies, Inc. Methods for firmware signature
US8795184B2 (en) 2010-07-12 2014-08-05 Rohm Co., Ltd. Wireless plethysmogram sensor unit, a processing unit for plethysmogram and a plethysmogram system
US8818725B2 (en) 2011-11-16 2014-08-26 Flextronics Ap, Llc Location information exchange between vehicle and device
US8508338B1 (en) 2010-11-07 2013-08-13 Howard Owen Fiddy Method and system for defeat of replay attacks against biometric authentication systems
US8756323B2 (en) 2010-11-26 2014-06-17 International Business Machines Corporation Semantic- and preference-based planning of cloud service templates
US8965957B2 (en) 2010-12-15 2015-02-24 Sap Se Service delivery framework
EP2668600A4 (en) 2011-01-27 2014-08-06 Computenext Inc Dynamically organizing cloud computing resources to facilitate discovery
EP2684311A1 (en) 2011-03-07 2014-01-15 Security First Corp. Secure file sharing method and system
US8370319B1 (en) 2011-03-08 2013-02-05 A9.Com, Inc. Determining search query specificity
US9576270B1 (en) 2011-05-06 2017-02-21 Extreme Networks, Inc. System and related method for management of devices of a network system via social media interfaces
US9064017B2 (en) * 2011-06-01 2015-06-23 D2L Corporation Systems and methods for providing information incorporating reinforcement-based learning and feedback
GB2492050A (en) 2011-06-13 2012-12-26 Torben Kuseler One-time multi-factor biometric representation for remote client authentication
US8850536B2 (en) 2011-08-05 2014-09-30 Safefaces LLC Methods and systems for identity verification in a social network using ratings
US8548207B2 (en) 2011-08-15 2013-10-01 Daon Holdings Limited Method of host-directed illumination and system for conducting host-directed illumination
US8515999B2 (en) 2011-09-29 2013-08-20 International Business Machines Corporation Method and system providing document semantic validation and reporting of schema violations
US9055121B2 (en) 2011-10-08 2015-06-09 Broadcom Corporation Social processing member offering fixed and intelligent services
US8452792B2 (en) 2011-10-28 2013-05-28 Microsoft Corporation De-focusing over big data for extraction of unknown value
US9952659B2 (en) 2011-11-08 2018-04-24 Microsoft Technology Licensing, Llc Presentation of multiple sources of application guidance information
WO2013075071A1 (en) 2011-11-18 2013-05-23 Ayman Hammad Mobile wallet store and service injection platform apparatuses, methods and systems
US8694439B2 (en) 2011-11-23 2014-04-08 Mohsin Shafique Shafique Method and system for a global goal based social networking
US8930886B2 (en) 2011-12-15 2015-01-06 Microsoft Corporation Identifying application resources through implicit application models
US9202105B1 (en) 2012-01-13 2015-12-01 Amazon Technologies, Inc. Image analysis for user authentication
US8819795B2 (en) 2012-02-01 2014-08-26 Amazon Technologies, Inc. Presenting managed security credentials to network sites
US9177169B2 (en) 2012-02-13 2015-11-03 Wwpass Corporation Secure digital storage
US20130226812A1 (en) 2012-02-24 2013-08-29 Mads Landrok Cloud proxy secured mobile payments
EP2823413A4 (en) 2012-03-07 2016-05-04 Snap Trends Inc Methods and systems of aggregating information of social networks based on geographical locations via a network
US9916589B2 (en) 2012-03-09 2018-03-13 Exponential Interactive, Inc. Advertisement selection using multivariate behavioral model
US10667790B2 (en) 2012-03-26 2020-06-02 Teratech Corporation Tablet ultrasound system
US20140129843A1 (en) 2012-11-02 2014-05-08 Weidong Shi Methods and Apparatus for Managing Service Access Using a Touch-Display Device Integrated with Fingerprint Imager
US8959358B2 (en) 2012-05-08 2015-02-17 Qualcomm Incorporated User-based identification system for social networks
US9710626B2 (en) 2012-07-06 2017-07-18 International Business Machines Corporation Security model for network information service
US10169571B1 (en) 2012-07-18 2019-01-01 Sequitur Labs, Inc. System and method for secure, policy-based access control for mobile computing devices
US9070024B2 (en) 2012-07-23 2015-06-30 International Business Machines Corporation Intelligent biometric identification of a participant associated with a media recording
CN103001945B (en) 2012-10-23 2015-04-15 中国科学院信息工程研究所 Diversified resource identifier safety access method
US20140189804A1 (en) * 2013-01-02 2014-07-03 Sap Ag Location-based application security mechanism
US8856541B1 (en) 2013-01-10 2014-10-07 Google Inc. Liveness detection
US9351688B2 (en) 2013-01-29 2016-05-31 Covidien Lp Low power monitoring systems and method
US9092601B2 (en) 2013-03-04 2015-07-28 Dell Products, Lp System and method for creating and managing object credentials for multiple applications
US9230081B2 (en) 2013-03-05 2016-01-05 Intel Corporation User authorization and presence detection in isolation from interference from and control by host central processing unit and operating system
US20140280955A1 (en) 2013-03-14 2014-09-18 Sky Socket, Llc Controlling Electronically Communicated Resources
US9473417B2 (en) 2013-03-14 2016-10-18 Airwatch Llc Controlling resources used by computing devices
US9721086B2 (en) 2013-03-15 2017-08-01 Advanced Elemental Technologies, Inc. Methods and systems for secure and reliable identity-based computing
US9378065B2 (en) 2013-03-15 2016-06-28 Advanced Elemental Technologies, Inc. Purposeful computing
US9904579B2 (en) 2013-03-15 2018-02-27 Advanced Elemental Technologies, Inc. Methods and systems for purposeful computing
US10075384B2 (en) 2013-03-15 2018-09-11 Advanced Elemental Technologies, Inc. Purposeful computing
US9448843B2 (en) * 2014-03-26 2016-09-20 International Business Machines Corporation Allocating a global resource to consumers across different regions of a distributed grid environment based on use data and demand data of each consumer
CA2958217A1 (en) 2014-09-13 2016-03-17 Advanced Elemental Technologies, Inc. Methods and systems for secure and reliable identity-based computing
KR101666374B1 (en) 2015-02-13 2016-10-14 크루셜텍 (주) Method, apparatus and computer program for issuing user certificate and verifying user
WO2016170625A1 (en) * 2015-04-22 2016-10-27 株式会社日立製作所 Computer system management system

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI574803B (en) * 2015-06-15 2017-03-21 車樂美縫衣機工業股份有限公司 Robot
US10226867B2 (en) 2015-06-15 2019-03-12 Janome Sewing Machine Co., Ltd. Robot
US20180349954A1 (en) * 2017-06-06 2018-12-06 Adobe Systems Incorporated Optimizing notification triggers for geo-fence communication systems

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