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Introducing search behavior into browsing based models of page's importance

Published: 13 May 2013 Publication History
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  • Abstract

    BrowseRank algorithm and its modifications are based on analyzing users' browsing trails. Our paper proposes a new method for computing page importance using a more realistic and effective search-aware model of user browsing behavior than the one used in BrowseRank.

    References

    [1]
    Y. Liu, B. Gao, T.-Y. Liu, Y. Zhang, Z. Ma, S. He, H. Li, BrowseRank: Letting Web Users Vote for Page Importance. Proc. SIGIR'08, pp. 451--458, 2008.
    [2]
    Y. Liu. T.-Y. Liu, B. Gao, Z. Ma, H. Li, A framework to compute page importance based on user behaviors, Inf Retrieval, 13: 22--45, 2010.
    [3]
    B. Gao, T.-Y. Liu, Z. Ma, T. Wang, H. Li, A General Markov Framework for Page Importance Computation, Proc. CIKM'09, pp. 1835--1838, 2009.
    [4]
    R. W. White, J. Huang. Assessing the Scenic Route: Measuring the Value of Search Trails in Web Logs, Proc. SIGIR'10, pp. 587--594, 2010.

    Cited By

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    • (2015)Efficient ranking based on web page importance and personalized search2015 International Conference on Communications and Signal Processing (ICCSP)10.1109/ICCSP.2015.7322671(1093-1097)Online publication date: Apr-2015

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    1. Introducing search behavior into browsing based models of page's importance

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        Published In

        cover image ACM Other conferences
        WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web
        May 2013
        1636 pages
        ISBN:9781450320382
        DOI:10.1145/2487788
        Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

        Sponsors

        • NICBR: Nucleo de Informatcao e Coordenacao do Ponto BR
        • CGIBR: Comite Gestor da Internet no Brazil

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 13 May 2013

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        Author Tags

        1. browserank
        2. page authority
        3. queries
        4. web search

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        • Poster

        Conference

        WWW '13
        Sponsor:
        • NICBR
        • CGIBR
        WWW '13: 22nd International World Wide Web Conference
        May 13 - 17, 2013
        Rio de Janeiro, Brazil

        Acceptance Rates

        WWW '13 Companion Paper Acceptance Rate 831 of 1,250 submissions, 66%;
        Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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        Cited By

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        • (2015)Efficient ranking based on web page importance and personalized search2015 International Conference on Communications and Signal Processing (ICCSP)10.1109/ICCSP.2015.7322671(1093-1097)Online publication date: Apr-2015

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