• DocumentCode
    3067037
  • Title

    Collaborative Filtering Recommendation Algorithm Based on Cloud Model Clustering of Multi-indicators Item Evaluation

  • Author

    Sa, Li

  • Author_Institution
    Liaoning Shiyou Univ., Fushun, China
  • fYear
    2011
  • fDate
    29-31 July 2011
  • Firstpage
    645
  • Lastpage
    648
  • Abstract
    Collaborative filtering recommendation algorithm is a personalized recommendation algorithm that is used widely in e-commerce recommendation system. In this paper, a collaborative filtering recomendation algorithm based on cloud model clustering of multi-indicators item evaluation is proposed. In the algorithm, the item evaluation is the object, time weighted function is introduced to item evaluation, soft culsters item based on cloud model and gets the recommended items. The algorithm solves problems of data updating and history validity of evaluation in the collaborative filtering algorithm. Soft cluster item based on cloud model is achieved to avoid the defects bringed by hard division.
  • Keywords
    electronic commerce; information filtering; recommender systems; cloud model clustering; collaborative filtering recommendation algorithm; e-commerce recommendation system; multiindicators item evaluation; personalized recommendation algorithm; soft cluster item; Algorithm design and analysis; Clustering algorithms; Collaboration; Filtering; Heuristic algorithms; Prediction algorithms; Real time systems; Collaborative filtering; cloud model clustering; item evaluation; multi-indicator; time_weighted;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business Computing and Global Informatization (BCGIN), 2011 International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4577-0788-9
  • Electronic_ISBN
    978-0-7695-4464-9
  • Type

    conf

  • DOI
    10.1109/BCGIn.2011.170
  • Filename
    6003982