A novel community structure detection algorithm for complex networks analysis based on Coulomb's law

  • Authors:

  • Jun Feng;Zhihua Zhang;Zhengxu Zhao;Zhiwei Gao;Lijia Liu

  • Affiliations:

  • School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, P.R. China;School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, P.R. China;School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, P.R. China;School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, P.R. China;School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, P.R. China

  • Venue:
  • AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
  • Year:
  • 2011

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Abstract

With the in-depth study of the physical meaning and mathematical characteristics of complex network, community structure is found as a common property for many networks. How to detect community structure is focused recently. In this paper, Coulomb's Law in physics is introduced to the community structure detecting in complex network. According to the law, we present a mathematical model of the community force, and take it as detecting evidence. The detection algorithm based on Coulomb's Law is proposed. Then we mainly study the relation among different engineering software information and establish the Engineering Software Format Network (ESFN). And in the experiment we apply the novel detection algorithm to this network compared with classical Girvan-Newman algorithm. With the high consistent rate, the Coulomb's Law-based algorithm has lower computation complexity than the classical algorithm. The experimental results show that the novel algorithm is effective and promising.