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Utilizing inter-passage and inter-document similarities for re-ranking search results

Published: 02 November 2009 Publication History

Abstract

We present a novel language-model-based approach to re-ranking an initially retrieved list so as to improve precision at top ranks. Our model integrates whole-document information with that induced from passages. Specifically, inter-passage, inter-document, and query-based similarities are integrated in our model. Empirical evaluation demonstrates the effectiveness of our approach.

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Cited By

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  • (2011)A study of the integration of passage-, document-, and cluster-based information for re-ranking search resultsInformation Retrieval10.1007/s10791-011-9168-614:6(593-616)Online publication date: 20-May-2011
  • (2010)Utilizing inter-passage and inter-document similarities for reranking search resultsACM Transactions on Information Systems (TOIS)10.1145/1877766.187776929:1(1-28)Online publication date: 27-Dec-2010

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  1. Utilizing inter-passage and inter-document similarities for re-ranking search results

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    cover image ACM Conferences
    CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management
    November 2009
    2162 pages
    ISBN:9781605585123
    DOI:10.1145/1645953
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    Published: 02 November 2009

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    Author Tags

    1. centrality
    2. language models
    3. passages
    4. re-ranking

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    View all
    • (2011)A study of the integration of passage-, document-, and cluster-based information for re-ranking search resultsInformation Retrieval10.1007/s10791-011-9168-614:6(593-616)Online publication date: 20-May-2011
    • (2010)Utilizing inter-passage and inter-document similarities for reranking search resultsACM Transactions on Information Systems (TOIS)10.1145/1877766.187776929:1(1-28)Online publication date: 27-Dec-2010

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