• DocumentCode
    2428398
  • Title

    Research on finding community structure based on filtration network model

  • Author

    Shen, Yi ; Pei, Wenjiang ; Li, Tao ; Liu, Jiming ; Yang, Lei ; Wang, Shaoping ; He, Zhenya

  • Author_Institution
    Dept. of Radio Eng., Southeast Univ., Nanjing
  • fYear
    2008
  • fDate
    7-11 June 2008
  • Firstpage
    20
  • Lastpage
    23
  • Abstract
    By defining community recursive coefficient M, we propose a new efficient algorithm called filtration split algorithm for discovering community structure in complex networks. By optimizing the M of child-networks based on dynamic recursive principle, the local communities are discovered automatically. Theoretical analysis and experiment results show that the algorithm can filtrate more than one edge once and make the networks split in parallel. For a network with n vertices, m edges, and c communities, the computation complexity is less than O((c+1)m+(c+1)). For many real-world networks are sparse m~n and c+1 Ltn, our algorithm can run in essentially linear time O((c+1)n).
  • Keywords
    computational complexity; parallel algorithms; child-network; community recursive coefficient; community structure; complex network; computation complexity; dynamic recursive principle; filtration network model; filtration split algorithm; linear time; parallel network; Complex networks; Computer networks; Distribution functions; Filtration; Helium; Joining processes; Neural networks; Signal processing; Signal processing algorithms; Symmetric matrices; Community Recursive Coefficient; Community Structure; Dynamic Recursive Principle; Filtration Split Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Signal Processing, 2008 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-2310-1
  • Electronic_ISBN
    978-1-4244-2311-8
  • Type

    conf

  • DOI
    10.1109/ICNNSP.2008.4590301
  • Filename
    4590301