Search result diversification based on hierarchical intents

Sha Hu, Zhicheng Dou, Xiaojie Wang, Tetsuya Sakai, Ji Rong Wen

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    35 Citations (Scopus)

    Abstract

    A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics.

    Original languageEnglish
    Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
    PublisherAssociation for Computing Machinery
    Pages63-72
    Number of pages10
    Volume19-23-Oct-2015
    ISBN (Print)9781450337946
    DOIs
    Publication statusPublished - 2015 Oct 17
    Event24th ACM International Conference on Information and Knowledge Management, CIKM 2015 - Melbourne, Australia
    Duration: 2015 Oct 192015 Oct 23

    Other

    Other24th ACM International Conference on Information and Knowledge Management, CIKM 2015
    CountryAustralia
    CityMelbourne
    Period15/10/1915/10/23

    Fingerprint

    Diversification
    Query
    Information needs
    Search engine
    Hierarchical structure
    Leverage

    Keywords

    • Hierarchical diversification
    • Hierarchical intents
    • Search result diversification

    ASJC Scopus subject areas

    • Business, Management and Accounting(all)
    • Decision Sciences(all)

    Cite this

    Hu, S., Dou, Z., Wang, X., Sakai, T., & Wen, J. R. (2015). Search result diversification based on hierarchical intents. In International Conference on Information and Knowledge Management, Proceedings (Vol. 19-23-Oct-2015, pp. 63-72). Association for Computing Machinery. https://doi.org/10.1145/2806416.2806455

    Search result diversification based on hierarchical intents. / Hu, Sha; Dou, Zhicheng; Wang, Xiaojie; Sakai, Tetsuya; Wen, Ji Rong.

    International Conference on Information and Knowledge Management, Proceedings. Vol. 19-23-Oct-2015 Association for Computing Machinery, 2015. p. 63-72.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Hu, S, Dou, Z, Wang, X, Sakai, T & Wen, JR 2015, Search result diversification based on hierarchical intents. in International Conference on Information and Knowledge Management, Proceedings. vol. 19-23-Oct-2015, Association for Computing Machinery, pp. 63-72, 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, Australia, 15/10/19. https://doi.org/10.1145/2806416.2806455
    Hu S, Dou Z, Wang X, Sakai T, Wen JR. Search result diversification based on hierarchical intents. In International Conference on Information and Knowledge Management, Proceedings. Vol. 19-23-Oct-2015. Association for Computing Machinery. 2015. p. 63-72 https://doi.org/10.1145/2806416.2806455
    Hu, Sha ; Dou, Zhicheng ; Wang, Xiaojie ; Sakai, Tetsuya ; Wen, Ji Rong. / Search result diversification based on hierarchical intents. International Conference on Information and Knowledge Management, Proceedings. Vol. 19-23-Oct-2015 Association for Computing Machinery, 2015. pp. 63-72
    @inproceedings{e4250e56b57d4493990ede28aecda4b6,
    title = "Search result diversification based on hierarchical intents",
    abstract = "A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics.",
    keywords = "Hierarchical diversification, Hierarchical intents, Search result diversification",
    author = "Sha Hu and Zhicheng Dou and Xiaojie Wang and Tetsuya Sakai and Wen, {Ji Rong}",
    year = "2015",
    month = "10",
    day = "17",
    doi = "10.1145/2806416.2806455",
    language = "English",
    isbn = "9781450337946",
    volume = "19-23-Oct-2015",
    pages = "63--72",
    booktitle = "International Conference on Information and Knowledge Management, Proceedings",
    publisher = "Association for Computing Machinery",

    }

    TY - GEN

    T1 - Search result diversification based on hierarchical intents

    AU - Hu, Sha

    AU - Dou, Zhicheng

    AU - Wang, Xiaojie

    AU - Sakai, Tetsuya

    AU - Wen, Ji Rong

    PY - 2015/10/17

    Y1 - 2015/10/17

    N2 - A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics.

    AB - A large percentage of queries issued to search engines are broad or ambiguous. Search result diversification aims to solve this problem, by returning diverse results that can fulfill as many different information needs as possible. Most existing intent-aware search result diversification algorithms formulate user intents for a query as a flat list of subtopics. In this paper, we introduce a new hierarchical structure to represent user intents and propose two general hierarchical diversification models to leverage hierarchical intents. Experimental results show that our hierarchical diversification models outperform state-of-the-art diversification methods that use traditional flat subtopics.

    KW - Hierarchical diversification

    KW - Hierarchical intents

    KW - Search result diversification

    UR - http://www.scopus.com/inward/record.url?scp=84958250435&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84958250435&partnerID=8YFLogxK

    U2 - 10.1145/2806416.2806455

    DO - 10.1145/2806416.2806455

    M3 - Conference contribution

    AN - SCOPUS:84958250435

    SN - 9781450337946

    VL - 19-23-Oct-2015

    SP - 63

    EP - 72

    BT - International Conference on Information and Knowledge Management, Proceedings

    PB - Association for Computing Machinery

    ER -