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An Improved SGN Algorithm Research for Detecting Community Structure in Complex Network

  • Pengfei Du
  • Yinghong Ma
  • Xiulong Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8351)

Abstract

In order to make more accurate partition community structure of complex networks, this paper puts forward a new community partition algorithm. The basic idea of the algorithm depends on node similarity, and it deletes the link whose similarity is the smallest every time, then takes modularity Q as the judging standard. Computing the corresponding modularity when network occurs into pieces, and the module structure is the ultimate community structure when Q reaches its peak. This algorithm not only improves the accuracy of the original algorithms, but also makes sure that the community structure has a better quantification. When the new algorithm is applied to the complex networks, we finally find that the algorithm is effective and feasible.

Keywords

complex network community structure node similarity modularity 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Pengfei Du
    • 1
    • 2
  • Yinghong Ma
    • 2
  • Xiulong Wang
    • 2
  1. 1.East of Wenhua Road No. 88Jinan, ShandongChina
  2. 2.School of Management Science and EngineeringShandong Normal UniversityJinanChina

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