• DocumentCode
    1800459
  • Title

    Community discovery algorithm based on coincidence degree

  • Author

    Xugang, Chen ; Hongzhi, Yu ; Tao, Xu ; Furong, Chang

  • Author_Institution
    Key Lab. of China´´s Nat. Linguistic Inf. Technol., Northwest Univ. for Nat., Lanzhou, China
  • Volume
    3
  • fYear
    2011
  • fDate
    24-26 Dec. 2011
  • Firstpage
    1437
  • Lastpage
    1439
  • Abstract
    Community structure is a structure characteristics commonly exists in all types of real network. To find out community in the network play an important role in understanding the function and behavior of the network. But the real network is changing all the time, the number of network community is changing with it, this characteristics is considered in the community discovery algorithm based on coincidence degree. The algorithm can accurately identify the network potential community by calculating and comparing the coincidence degree of network nodes and the modularity between communities.
  • Keywords
    information networks; network theory (graphs); pattern clustering; coincidence degree; community discovery algorithm; community structure; network behavior; network function; network potential community identification; Biology; Communities; coincidence degree; community discovery; modularity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2011 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4577-1586-0
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2011.6182235
  • Filename
    6182235
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1800459