CA2310321A1 - Method and system for determining approximate hamming distance and approximate nearest neighbors in an electronic storage device - Google Patents

Method and system for determining approximate hamming distance and approximate nearest neighbors in an electronic storage device Download PDF

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Publication number
CA2310321A1
CA2310321A1 CA002310321A CA2310321A CA2310321A1 CA 2310321 A1 CA2310321 A1 CA 2310321A1 CA 002310321 A CA002310321 A CA 002310321A CA 2310321 A CA2310321 A CA 2310321A CA 2310321 A1 CA2310321 A1 CA 2310321A1
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CA
Canada
Prior art keywords
trace
database
hamming distance
approximate
query
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CA002310321A
Other languages
French (fr)
Other versions
CA2310321C (en
Inventor
Rafail Ostrovsky
Yuval Rabani
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Telcordia Licensing Co LLC
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Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Publication of CA2310321A1 publication Critical patent/CA2310321A1/en
Application granted granted Critical
Publication of CA2310321C publication Critical patent/CA2310321C/en
Anticipated expiration legal-status Critical
Expired - Fee Related legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/90335—Query processing
    • G06F16/90344—Query processing by using string matching techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24147—Distances to closest patterns, e.g. nearest neighbour classification
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99935—Query augmenting and refining, e.g. inexact access

Abstract

A method and system identify in a database one or more data entries that are the nearest neighbors of a query. The database prebuilds a first set of strings by probabilistically selecting values of respective bits in each of the first set of strings based on a probability that depends on a first hamming distance. Based on the first set of strings, the database predetermines the trace values of each data entry in the database, respectively, and stores the predetermined trace values as entries in a trace table. For each trace value entry, the database identifies the data entries whose trace values are within a second hamming distance of the trace value entry, and stores the addresses of the identified data entries in the trace value entry. When the database receives a query, by identifying the trace value entry in the trace table that match the tract value of the query, the database identifies the data entries that are within the first hamming distance of the query. In addition, a method and system estimate the hamming distance between two strings in a network.
CA002310321A 1997-11-17 1998-11-17 Method and system for determining approximate hamming distance and approximate nearest neighbors in an electronic storage device Expired - Fee Related CA2310321C (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US6693697P 1997-11-17 1997-11-17
US60/066,936 1997-11-17
PCT/US1998/024452 WO1999026235A2 (en) 1997-11-17 1998-11-17 Method and system for determining approximate hamming distance and approximate nearest neighbors in an electronic storage device

Publications (2)

Publication Number Publication Date
CA2310321A1 true CA2310321A1 (en) 1999-05-27
CA2310321C CA2310321C (en) 2004-11-16

Family

ID=22072682

Family Applications (1)

Application Number Title Priority Date Filing Date
CA002310321A Expired - Fee Related CA2310321C (en) 1997-11-17 1998-11-17 Method and system for determining approximate hamming distance and approximate nearest neighbors in an electronic storage device

Country Status (3)

Country Link
US (1) US6226640B1 (en)
CA (1) CA2310321C (en)
WO (1) WO1999026235A2 (en)

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US6446068B1 (en) * 1999-11-15 2002-09-03 Chris Alan Kortge System and method of finding near neighbors in large metric space databases
US7305380B1 (en) 1999-12-15 2007-12-04 Google Inc. Systems and methods for performing in-context searching
US7318053B1 (en) * 2000-02-25 2008-01-08 International Business Machines Corporation Indexing system and method for nearest neighbor searches in high dimensional data spaces
US7227511B2 (en) * 2000-04-24 2007-06-05 Microsoft Corporation Method for activating an application in context on a remote input/output device
US7030837B1 (en) * 2000-04-24 2006-04-18 Microsoft Corporation Auxiliary display unit for a computer system
US6917373B2 (en) * 2000-12-28 2005-07-12 Microsoft Corporation Context sensitive labels for an electronic device
US6611837B2 (en) * 2000-06-05 2003-08-26 International Business Machines Corporation System and method for managing hierarchical objects
US6931393B1 (en) * 2000-06-05 2005-08-16 International Business Machines Corporation System and method for enabling statistical matching
US7010606B1 (en) 2000-06-05 2006-03-07 International Business Machines Corporation System and method for caching a network connection
US6745189B2 (en) * 2000-06-05 2004-06-01 International Business Machines Corporation System and method for enabling multi-indexing of objects
US6963876B2 (en) * 2000-06-05 2005-11-08 International Business Machines Corporation System and method for searching extended regular expressions
US6823328B2 (en) * 2000-06-05 2004-11-23 International Business Machines Corporation System and method for enabling unified access to multiple types of data
US7016917B2 (en) * 2000-06-05 2006-03-21 International Business Machines Corporation System and method for storing conceptual information
US6950855B2 (en) * 2002-01-18 2005-09-27 International Business Machines Corporation Master node selection in clustered node configurations
US6909358B2 (en) * 2002-03-21 2005-06-21 International Business Machines Corporation Hamming distance comparison
US7817820B2 (en) * 2003-11-25 2010-10-19 Florida State University Method and system for generating and using digital fingerprints for electronic documents
WO2006094016A2 (en) 2005-02-28 2006-09-08 The Regents Of The University Of California Method for low distortion embedding of edit distance to hamming distance
US8818980B2 (en) * 2010-01-12 2014-08-26 Intouchlevel Corporation Connection engine
US8543598B2 (en) * 2010-03-01 2013-09-24 Microsoft Corporation Semantic object characterization and search
CN103020321B (en) * 2013-01-11 2015-08-19 广东图图搜网络科技有限公司 Neighbor search method and system
US10496900B2 (en) * 2013-05-08 2019-12-03 Seagate Technology Llc Methods of clustering computational event logs
JP6187237B2 (en) * 2013-12-19 2017-08-30 富士通株式会社 Document image retrieval apparatus, method, and program
US10489589B2 (en) 2016-11-21 2019-11-26 Cylance Inc. Anomaly based malware detection
US10496706B2 (en) 2017-04-17 2019-12-03 International Business Machines Corporation Matching strings in a large relational database
US11593412B2 (en) 2019-07-22 2023-02-28 International Business Machines Corporation Providing approximate top-k nearest neighbours using an inverted list

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FR2293741A1 (en) * 1974-12-04 1976-07-02 Anvar METHOD AND SYSTEM FOR ITERATIVE AND SIMULTANEOUS RECONCILIATION OF DATA WITH A SET OF REFERENCE DATA
US4084260A (en) * 1976-07-12 1978-04-11 Sperry Rand Corporation Best match content addressable memory
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US5870754A (en) * 1996-04-25 1999-02-09 Philips Electronics North America Corporation Video retrieval of MPEG compressed sequences using DC and motion signatures
US5890151A (en) * 1997-05-09 1999-03-30 International Business Machines Corporation Method and system for performing partial-sum queries on a data cube

Also Published As

Publication number Publication date
WO1999026235A2 (en) 1999-05-27
CA2310321C (en) 2004-11-16
US6226640B1 (en) 2001-05-01

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