• DocumentCode
    3073101
  • Title

    A Hybrid Collaborative Filtering Recommendation Algorithm for Solving the Data Sparsity

  • Author

    He, Ying ; Yang, Shaoyu ; Jiao, Chenbin

  • Author_Institution
    Henan Bus. Coll., Zhengzhou, China
  • fYear
    2011
  • fDate
    16-17 July 2011
  • Firstpage
    118
  • Lastpage
    121
  • Abstract
    With the huge electronic data´s explosion in the commercial and the service area, the collaborative filtering technology attracts many of researchers´ attention. In this paper, we provide a hybrid collaborative filtering recommendation algorithm, which based on the research and analyses for the data sparsity and the similarity accuracy. The simulation result indicates that the algorism can solve effectively the extreme data sparsity and promote the similarity accuracy in collaborative filtering.
  • Keywords
    data handling; information filtering; recommender systems; data sparsity; electronic data explosion; hybrid collaborative filtering recommendation algorithm; Accuracy; Bayesian methods; Collaboration; Data models; Filling; Filtering; Predictive models; collaborative filtering algorism [CFA]; data sparsity; recommend system [RS];
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Society (ISCCS), 2011 International Symposium on
  • Conference_Location
    Kota Kinabalu
  • Print_ISBN
    978-1-4577-0644-8
  • Type

    conf

  • DOI
    10.1109/ISCCS.2011.40
  • Filename
    6004281