• DocumentCode
    2293506
  • Title

    User interest modeling based on large item-set group

  • Author

    Liao, Kaiji ; Ye, Donghai ; Xiong, Huihui

  • Author_Institution
    Sch. of Bus. Adm., South China Univ. of Technol., Guangzhou, China
  • Volume
    8
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    4400
  • Lastpage
    4404
  • Abstract
    In order to solve the issue of data sparsity and user´s multiple interests which exist in the practical application, we proposes a kind of user interest modeling method based on the large item-set group. The mapping relationship between the items and the user evaluations is transformed into the one between the item properties and the user evaluations to solve the problem of data sparsity; the large item-set group is used to solve the problem of user´s multiple interests. This modeling method has been verified by collecting data from www.douban.com. The results showed that our recommended method based on the large item-set group can effectively reduce the difference level between the target users and the recommended knowledge, comparing with other current recommended methods.
  • Keywords
    user modelling; data sparsity; item properties; large item-set group; mapping relationship; user evaluation; user interest modeling; Algorithm design and analysis; Data models; Films; Filtering; Heuristic algorithms; Motion pictures; Prediction algorithms; Data sparsity; Large item-set group; Similarity; User interest;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583518
  • Filename
    5583518