Inferring user interests from relevance feedback with high similarity sequence data-driven clustering

Roman Y. Shtykh, Qun Jin

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

    1 Citation (Scopus)

    Abstract

    Relevance feedback is an important source of information about a user and often used for usage and user modeling for further personalization of usersystem interactions. In this paper we present a method to infer the user's interests from his/her relevance feedback using an online incremental clustering method. For inference of a new interest (concept) and concept update the method uses the similarity characteristics of uniform user relevance feedback. It is fast, easy to implement and gives reasonable clustering results. We evaluate the method against two different data sets, demonstrate and discuss the outcomes.

    Original languageEnglish
    Title of host publicationProceedings of the 2nd International Symposium on Universal Communication, ISUC 2008
    Pages390-396
    Number of pages7
    DOIs
    Publication statusPublished - 2008
    Event2nd International Symposium on Universal Communication, ISUC 2008 - Osaka
    Duration: 2008 Dec 152008 Dec 16

    Other

    Other2nd International Symposium on Universal Communication, ISUC 2008
    CityOsaka
    Period08/12/1508/12/16

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    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Information Systems
    • Software

    Cite this

    Shtykh, R. Y., & Jin, Q. (2008). Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. In Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008 (pp. 390-396). [4724491] https://doi.org/10.1109/ISUC.2008.39

    Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. / Shtykh, Roman Y.; Jin, Qun.

    Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008. 2008. p. 390-396 4724491.

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

    Shtykh, RY & Jin, Q 2008, Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. in Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008., 4724491, pp. 390-396, 2nd International Symposium on Universal Communication, ISUC 2008, Osaka, 08/12/15. https://doi.org/10.1109/ISUC.2008.39
    Shtykh RY, Jin Q. Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. In Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008. 2008. p. 390-396. 4724491 https://doi.org/10.1109/ISUC.2008.39
    Shtykh, Roman Y. ; Jin, Qun. / Inferring user interests from relevance feedback with high similarity sequence data-driven clustering. Proceedings of the 2nd International Symposium on Universal Communication, ISUC 2008. 2008. pp. 390-396
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