• DocumentCode
    2244945
  • Title

    Active fuzzy clustering for collaborative filtering

  • Author

    Srinivasa, N. ; Medasani, S.

  • Author_Institution
    LLC, HRL Laboratories, Malibu, CA, USA
  • Volume
    3
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    1697
  • Abstract
    We present a fuzzy clustering approach to collaborative filtering. Our approach allows for users to be clustered into multiple user groups. Furthermore, our approach is active in that it can rapidly adapt to both short and long term user interest changes. Our approach is capable of on-line collaborative filtering with simultaneous clustering at the document content level, user group level, as well as document clustering based on similarity of user interests. We demonstrate the various features of the approach using a synthetic example.
  • Keywords
    filtering theory; fuzzy set theory; pattern clustering; active fuzzy clustering approach; document clustering; document content level; multiple user groups; online collaborative filtering; user group level; Clustering algorithms; Collaboration; Collaborative work; Content based retrieval; Filtering; Fuzzy neural networks; Fuzzy systems; Laboratories; Neural networks; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
  • ISSN
    1098-7584
  • Print_ISBN
    0-7803-8353-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.2004.1375436
  • Filename
    1375436