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Query expansion using explicit semantic analysis

Published: 09 September 2012 Publication History

Abstract

Query expansion is a technique utilized within information retrieval to solve word mismatch between queries and document. In previous method, expansion words are usually selected by counting word co-occurrences in the documents. However, word co-occurrences are not always a good indicator for relevance, whereas some are background words of the whole collection. In order to select good expansion words, explicit semantic analysis (ESA) is adopted in our model to estimate two kinds of relevance weight. One is the relevance weight between query and its relevant word extracted from the top-ranked documents in initial retrieval results. The other is the relevance weight between each query word and its relevant words extracted from the snapshot of Google search result when that query word is used as search keyword. The estimated relevance weights are used to select good expansion words for second retrieval. The experiments on the three test collections show that our expansion words selection model is more effective than the standard Rocchio expansion.

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Cited By

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  • (2018)Hybrid query expansion model for text and microblog information retrievalInformation Retrieval Journal10.1007/s10791-017-9326-621:4(337-367)Online publication date: 3-Feb-2018
  • (2018)Supporting requirements to code traceability through refactoringRequirements Engineering10.1007/s00766-013-0197-019:3(309-329)Online publication date: 24-Dec-2018
  • (2016)A query expansion approach for social media data extractionInternational Journal of Web and Grid Services10.1504/IJWGS.2016.08014212:4(418-441)Online publication date: 1-Jan-2016

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  1. Query expansion using explicit semantic analysis

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    cover image ACM Other conferences
    ICIMCS '12: Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
    September 2012
    243 pages
    ISBN:9781450316002
    DOI:10.1145/2382336
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • National Science Foundation of China
    • CCNU: Central China Normal University
    • Daqian Vision: Daqian Vision
    • Microsoft Research: Microsoft Research
    • Beijing ACM SIGMM Chapter
    • NEC: NEC Labs China

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 09 September 2012

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    Author Tags

    1. ESA
    2. information retrieval
    3. query expansion
    4. relevant words

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    ICIMCS '12
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    • CCNU
    • Daqian Vision
    • Microsoft Research
    • NEC

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    Overall Acceptance Rate 163 of 456 submissions, 36%

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    Cited By

    View all
    • (2018)Hybrid query expansion model for text and microblog information retrievalInformation Retrieval Journal10.1007/s10791-017-9326-621:4(337-367)Online publication date: 3-Feb-2018
    • (2018)Supporting requirements to code traceability through refactoringRequirements Engineering10.1007/s00766-013-0197-019:3(309-329)Online publication date: 24-Dec-2018
    • (2016)A query expansion approach for social media data extractionInternational Journal of Web and Grid Services10.1504/IJWGS.2016.08014212:4(418-441)Online publication date: 1-Jan-2016

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