• DocumentCode
    2798993
  • Title

    A Research on Fuzzy Formal Concept Analysis Based Collaborative Filtering Recommendation System

  • Author

    Fang, Peici ; Zheng, Siyao

  • Author_Institution
    Sch. of Comput. Sci. & Eng., BeiHang Univ., Beijing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    Nov. 30 2009-Dec. 1 2009
  • Firstpage
    352
  • Lastpage
    355
  • Abstract
    A novel method for collaborative filtering recommendation based on fuzzy formal concept analysis is proposed in this paper, including the algorithm for user rating matrix fuzzification, the algorithm generating fuzzy concept for rating prediction and the algorithm generating predicting rating. Fuzzy formal concept analysis is a means of conceptual clustering, it not only solves the high sparsity problem of user rating matrix, but also be more efficient when the matrix is more sparse. Sharp edge problem is also solved because of the introduction of fuzzy logic. The experiment applied on a common used Movielens database shows the reasonable accuracy and time efficiency of the proposed collaborative filtering recommendation system.
  • Keywords
    fuzzy set theory; matrix algebra; recommender systems; collaborative filtering recommendation system; fuzzy formal concept analysis; fuzzy logic; sharp edge problem; sparsity problem; user rating matrix fuzzification; Algorithm design and analysis; Clustering algorithms; Collaboration; Filtering algorithms; Fuzzy logic; Fuzzy sets; Fuzzy systems; History; Motion pictures; Sparse matrices; collaborative filtering recommendation; formal concept analysis; fuzzy concept analysis; fuzzy logic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3888-4
  • Type

    conf

  • DOI
    10.1109/KAM.2009.40
  • Filename
    5362282