BIROn - Birkbeck Institutional Research Online

    On the equilibrium of query reformulation and document retrieval

    Zou, S. and Tao, G. and Wang, J. and Zhang, W. and Zhang, Dell (2018) On the equilibrium of query reformulation and document retrieval. In: UNSPECIFIED (ed.) Proceedings of the 4th ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR). ACM, pp. 43-50. ISBN 9781450344906.

    [img]
    Preview
    Text
    dellzhang_ictir2018.pdf

    Download (1MB) | Preview

    Abstract

    In this paper, we study jointly query reformulation and document relevance estimation, the two essential aspects of information retrieval (IR). Their interactions are modelled as a two-player strategic game: one player, a query formulator, taking actions to produce the optimal query, is expected to maximize its own utility with respect to the relevance estimation of documents produced by the other player, a retrieval modeler; simultaneously, the retrieval modeler, taking actions to produce the document relevance scores, needs to optimize its likelihood from the training data with respect to the refined query produced by the query formulator. Their equilibrium or equilibria will be reached when both are the best responses to each other. We derive our equilibrium theory of IR using normal-form representations: when a standard relevance feedback algorithm is coupled with a retrieval model, they would share the same objective function and thus form a partnership game; by contrast, pseudo relevance feedback pursues a rather different objective than that of retrieval models, therefore the interaction between them would lead to a general-sum game (though implicitly collaborative). Our game-theoretical analyses not only yield useful insights into the two major aspects of IR, but also offer new practical algorithms for achieving the equilibrium state of retrieval which have been shown to bring consistent performance improvements in both text retrieval and item recommendation.

    Metadata

    Item Type: Book Section
    Additional Information: (c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Keyword(s) / Subject(s): relevance feedback, retrieval model, game theory
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Dr Dell Zhang
    Date Deposited: 16 Nov 2018 09:40
    Last Modified: 26 Jul 2019 16:35
    URI: http://eprints.bbk.ac.uk/id/eprint/23961

    Statistics

    Downloads
    Activity Overview
    87Downloads
    45Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item