• DocumentCode
    536224
  • Title

    An algorithm for communication community organizational structure analysis

  • Author

    Hou, Ying ; Shen, Hao-Xiang ; Liu, Li-Xiong ; Huang, Hai

  • Author_Institution
    Nat. Digital Switching Syst. Eng. & Technol. Res. Center, Zhengzhou, China
  • Volume
    2
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    609
  • Lastpage
    613
  • Abstract
    The purpose of communication community structure detection in a network is to cluster weighted complex network. By learning from traditional clustering algorithm, OPTICS, an algorithm is designed to detect communication community and analyze its structure. This algorithm considers the effect and detects communication community based on its communication intensity. The detection result is organized in multi distinguishing granular to provide hierarchical structural organization in the communication community. Experiments showed that this algorithm is effective in detecting communication community and analyzing organizational structure.
  • Keywords
    complex networks; network theory (graphs); pattern clustering; telecommunication computing; OPTICS; communication community structure detection; communication intensity; complex network; learning algorithm; network cluster; organizational structure analysis; Biology; Biomedical optical imaging; Communities; Gallium nitride; Optical fiber networks; community detection; complex network; organizational structure analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658415
  • Filename
    5658415