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Complete graph model for community detection

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  • Sun, Peng Gang
  • Sun, Xiya

Abstract

Community detection brings plenty of considerable problems, which has attracted more attention for many years. This paper develops a new framework, which tries to measure the interior and the exterior of a community based on a same metric, complete graph model. In particular, the exterior is modeled as a complete bipartite. We partition a network into subnetworks by maximizing the difference between the interior and the exterior of the subnetworks. In addition, we compare our approach with some state of the art methods on computer-generated networks based on the LFR benchmark as well as real-world networks. The experimental results indicate that our approach obtains better results for community detection, is capable of splitting irregular networks and achieves perfect results on the karate network and the dolphin network.

Suggested Citation

  • Sun, Peng Gang & Sun, Xiya, 2017. "Complete graph model for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 88-97.
    • Handle: RePEc:eee:phsmap:v:471:y:2017:i:c:p:88-97
    DOI: 10.1016/j.physa.2016.12.014
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    References listed on IDEAS

    as
    1. Sun, Peng Gang, 2014. "Weighting links based on edge centrality for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 346-357.
    2. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    3. Du, Wen-Bo & Zhou, Xing-Lian & Lordan, Oriol & Wang, Zhen & Zhao, Chen & Zhu, Yan-Bo, 2016. "Analysis of the Chinese Airline Network as multi-layer networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 108-116.
    4. Sun, Peng Gang, 2016. "Imbalance problem in community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 364-376.
    5. Du, Wen-Bo & Gao, Yang & Liu, Chen & Zheng, Zheng & Wang, Zhen, 2015. "Adequate is better: particle swarm optimization with limited-information," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 832-838.
    6. Martin Rosvall & Carl T Bergstrom, 2011. "Multilevel Compression of Random Walks on Networks Reveals Hierarchical Organization in Large Integrated Systems," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-10, April.
    7. Sun, Peng Gang & Yang, Yang, 2013. "Methods to find community based on edge centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 1977-1988.
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    Cited by:

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    3. Manuel Guerrero & Consolación Gil & Francisco G. Montoya & Alfredo Alcayde & Raúl Baños, 2020. "Multi-Objective Evolutionary Algorithms to Find Community Structures in Large Networks," Mathematics, MDPI, vol. 8(11), pages 1-18, November.

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