• DocumentCode
    1175640
  • Title

    Collaborative filtering with maximum entropy

  • Author

    Pavlov, Dmitry ; Manavoglu, Eren ; Giles, C. Lee ; Pennock, David M.

  • Volume
    19
  • Issue
    6
  • fYear
    2004
  • Firstpage
    40
  • Lastpage
    47
  • Abstract
    As users navigate through online document collections on high-volume Web servers, they depend on good recommendations. We present a novel maximum-entropy algorithm for generating accurate recommendations and a data-clustering approach for speeding up model training. Recommender systems attempt to automate the process of "word of mouth" recommendations within a community. Typical application environments such as online shops and search engines have many dynamic aspects.
  • Keywords
    Internet; document handling; information filtering; information filters; maximum entropy methods; search engines; Web servers; collaborative filtering; data-clustering approach; maximum entropy algorithm; online document collection; recommender systems; search engines; Bayesian methods; Collaboration; Collaborative work; Computer science; Context modeling; Entropy; Filtering; History; Navigation; Search engines; maximum entropy model; mixture models; recommender systems; sequence modeling;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2004.59
  • Filename
    1363733
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1175640