• DocumentCode
    736402
  • Title

    Community discovery algorithm based on potential energy in complex network

  • Author

    Shuangshuang, Liu ; Hong, Wang

  • Author_Institution
    School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China
  • fYear
    2015
  • fDate
    28-30 July 2015
  • Firstpage
    1246
  • Lastpage
    1251
  • Abstract
    In recent years, our understanding of complex networks has improved. Community structure as a common characteristic of complex networks has become an important direction in the study of complex networks. Meanwhile, people put forward many community detection algorithms. To original Largest Fitness Measure algorithm, the selection of seed node is random, community division needs to be improved, and it is difficult to achieve its end condition. Based on above problems, we propose a kind of Weight Largest Fitness Measure algorithm. According to the thought of potential energy, the new algorithm optimizes and handles initial node, simplify node fitness function and expand community according to potential queue. Finally, through two groups of experimental validate the performance of the algorithm. The experimental results show that, compared with Largest Fitness Measure algorithm, the new algorithm has higher accuracy and shorter run time.
  • Keywords
    Algorithm design and analysis; Complex networks; Electronic mail; Gravity; Potential energy; Social network services; Software algorithms; Community Detection; Complex Network; Potential Energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2015 34th Chinese
  • Conference_Location
    Hangzhou, China
  • Type

    conf

  • DOI
    10.1109/ChiCC.2015.7259812
  • Filename
    7259812