• DocumentCode
    2910292
  • Title

    Engene: A genetic algorithm classifier for content-based recommender systems that does not require continuous user feedback

  • Author

    Pagonis, John ; Clark, Adrian F.

  • Author_Institution
    Pragmaticomm Ltd., Hemel Hempstead, UK
  • fYear
    2010
  • fDate
    8-10 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    We present Engene, a genetic algorithm based classifier which is designed for use in content-based recommender systems. Once bootstrapped Engene does not need any human feedback. Although it is primarily used as an on-line classifier, in this paper we present its use as a one-class document batch classifier and compare its performance against that of a one-class k-NN classifier.
  • Keywords
    content-based retrieval; genetic algorithms; pattern classification; recommender systems; text analysis; bootstrapped Engene; content-based recommender system; genetic algorithm classifier; one-class document batch classifier; online classifier; textual content classifier; user feedback; Gallium; Variable speed drives;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2010 UK Workshop on
  • Conference_Location
    Colchester
  • Print_ISBN
    978-1-4244-8774-5
  • Electronic_ISBN
    978-1-4244-8773-8
  • Type

    conf

  • DOI
    10.1109/UKCI.2010.5625594
  • Filename
    5625594