• DocumentCode
    3430587
  • Title

    A new K-means algorithm for community structures detection based on fuzzy clustering

  • Author

    Liu, Qun ; Peng, Zhiming ; Gao, Yi ; Liu, Qian

  • Author_Institution
    Chongqing key laboratory of computational intelligence, Chongqing University of Posts and Telecommunications, China
  • fYear
    2012
  • fDate
    11-13 Aug. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Finding community structures from networks is one of the most popular research areas in recent years. Because of the shortcoming of FCM, for example, its results depend on the initial center node and need to specify the community number, based on the fuzzy theory, an improved FCM algorithm(NKFCM) is proposed, which can get the number of communities and the community centers automatically. NKFCM is used to find the communities of network. The experiments in real networks show that this method can get better results.
  • Keywords
    Biology; Biomedical optical imaging; Communities; Image edge detection; Laboratories; Community structure; Fuzzy C-Means clustering; K-means algorithm; Social network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2012 IEEE International Conference on
  • Conference_Location
    Hangzhou, China
  • Print_ISBN
    978-1-4673-2310-9
  • Type

    conf

  • DOI
    10.1109/GrC.2012.6468579
  • Filename
    6468579