People like us: Mining scholarly data for comparable researchers

Graham Cormode, S. Muthukrishnan, Jinyun Yan

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

    Abstract

    We present the problem of finding comparable researchers for any given researcher. This problem has many motivations. Firstly, know thyself. The answers of where we stand among research community and who we are most alike may not be easily found by existing evaluations of ones' research mainly based on citation counts. Secondly, there are many situations where one needs to find comparable researchers e.g., for reviewing peers, constructing programming committees or compiling teams for grants. It is often done through an ad hoc and informal basis. Utilizing the large scale scholarly data accessible on the web, we address the problem of automatically finding comparable researchers. We propose a standard to quantify the quality of research output, via the quality of publishing venues. We represent a researcher as a sequence of her publication records, and develop a framework of comparison of researchers by sequence matching. Several variations of comparisons are considered including matching by quality of publication venue and research topics, and performing prefix matching. We evaluate our methods on a large corpus and demonstrate the effectiveness of our methods through examples. In the end, we identify several promising directions for further work.

    Original languageEnglish (US)
    Title of host publicationWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
    PublisherAssociation for Computing Machinery, Inc
    Pages1227-1232
    Number of pages6
    ISBN (Electronic)9781450327459
    DOIs
    StatePublished - Apr 7 2014
    Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
    Duration: Apr 7 2014Apr 11 2014

    Publication series

    NameWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

    Conference

    Conference23rd International Conference on World Wide Web, WWW 2014
    CountryKorea, Republic of
    CitySeoul
    Period4/7/144/11/14

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    Keywords

    • Comparison
    • Publications
    • Reputation

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Software

    Cite this

    Cormode, G., Muthukrishnan, S., & Yan, J. (2014). People like us: Mining scholarly data for comparable researchers. In WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web (pp. 1227-1232). (WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web). Association for Computing Machinery, Inc. https://doi.org/10.1145/2567948.2579038