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    How to count thumb-ups and thumb-downs: user-rating based ranking of items from an axiomatic perspective

    Zhang, Dell and Mao, R. and Li, H. and Mao, J. (2011) How to count thumb-ups and thumb-downs: user-rating based ranking of items from an axiomatic perspective. In: Amati, G. and Crestani, F. (eds.) Advances in Information Retrieval Theory. Lecture Notes In Computer Science 6931. Berlin, Germany: Springer, pp. 238-249. ISBN 9783642233173.

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    Abstract

    It is a common practice among Web 2.0 services to allow users to rate items on their sites. In this paper, we first point out the flaws of the popular methods for user-rating based ranking of items, and then argue that two well-known Information Retrieval (IR) techniques, namely the Probability Ranking Principle and Statistical Language Modelling, provide simple but effective solutions to this problem. Furthermore, we examine the existing and proposed methods in an axiomatic framework, and prove that only the score functions given by the Dirichlet Prior smoothing method as well as its special cases can satisfy both of the two axioms borrowed from economics.

    Metadata

    Item Type: Book Section
    Additional Information: Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011. Proceedings
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Administrator
    Date Deposited: 30 May 2013 11:26
    Last Modified: 02 Dec 2016 13:26
    URI: http://eprints.bbk.ac.uk/id/eprint/7092

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