WO2006132793A3 - Learning facts from semi-structured text - Google Patents

Learning facts from semi-structured text Download PDF

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Publication number
WO2006132793A3
WO2006132793A3 PCT/US2006/019807 US2006019807W WO2006132793A3 WO 2006132793 A3 WO2006132793 A3 WO 2006132793A3 US 2006019807 W US2006019807 W US 2006019807W WO 2006132793 A3 WO2006132793 A3 WO 2006132793A3
Authority
WO
WIPO (PCT)
Prior art keywords
facts
semi
identified
structured text
instances
Prior art date
Application number
PCT/US2006/019807
Other languages
French (fr)
Other versions
WO2006132793A2 (en
Inventor
Shubin Zhao
Jonathan T Betz
Original Assignee
Google Inc
Shubin Zhao
Jonathan T Betz
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 Google Inc, Shubin Zhao, Jonathan T Betz filed Critical Google Inc
Priority to CN2006800280576A priority Critical patent/CN101253498B/en
Priority to EP06784449A priority patent/EP1891557A2/en
Priority to CA2610208A priority patent/CA2610208C/en
Publication of WO2006132793A2 publication Critical patent/WO2006132793A2/en
Publication of WO2006132793A3 publication Critical patent/WO2006132793A3/en

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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
    • G06F16/80—Information retrieval; Database structures therefor; File system structures therefor of semi-structured data, e.g. markup language structured data such as SGML, XML or HTML
    • G06F16/84—Mapping; Conversion
    • 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
    • G06F16/93—Document management systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • G06F16/353—Clustering; Classification into predefined classes
    • 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
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • 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
    • Y10S707/953—Organization of data
    • Y10S707/962—Entity-attribute-value

Abstract

A method and system of learning, or bootstrapping, facts from semi-structured text is described. Starting with a set of seed facts associated with an object, documents associated with the object are identified. The identified documents are checked to determine if each has at least a first predefined number of seed facts. If a document does have at least a first predefined number of seed facts, a contextual pattern associated with the seed facts is identified and other instances of content in the document matching the contextual pattern are identified. If the document includes at least a second predefined number of the other instances of content matching the contextual pattern, then facts may be extracted from the other instances.
PCT/US2006/019807 2005-05-31 2006-05-18 Learning facts from semi-structured text WO2006132793A2 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CN2006800280576A CN101253498B (en) 2005-05-31 2006-05-18 Learning facts from semi-structured text
EP06784449A EP1891557A2 (en) 2005-05-31 2006-05-18 Learning facts from semi-structured text
CA2610208A CA2610208C (en) 2005-05-31 2006-05-18 Learning facts from semi-structured text

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US11/142,853 2005-05-31
US11/142,853 US7769579B2 (en) 2005-05-31 2005-05-31 Learning facts from semi-structured text

Publications (2)

Publication Number Publication Date
WO2006132793A2 WO2006132793A2 (en) 2006-12-14
WO2006132793A3 true WO2006132793A3 (en) 2007-02-08

Family

ID=37309560

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2006/019807 WO2006132793A2 (en) 2005-05-31 2006-05-18 Learning facts from semi-structured text

Country Status (5)

Country Link
US (4) US7769579B2 (en)
EP (1) EP1891557A2 (en)
CN (1) CN101253498B (en)
CA (1) CA2610208C (en)
WO (1) WO2006132793A2 (en)

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Publication number Priority date Publication date Assignee Title
JP7197531B2 (en) 2020-03-19 2022-12-27 ヤフー株式会社 Information processing device, information processing system, information processing method, and program

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