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Deep community detection in topologically incomplete networks

Author

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  • Xin, Xin
  • Wang, Chaokun
  • Ying, Xiang
  • Wang, Boyang

Abstract

In this paper, we consider the problem of detecting communities in topologically incomplete networks (TIN), which are usually observed from real-world networks and where some edges are missing. Existing approaches to community detection always consider the input network as connected. However, more or less, even nearly all, edges are missing in real-world applications, e.g. the protein–protein interaction networks. Clearly, it is a big challenge to effectively detect communities in these observed TIN.

Suggested Citation

  • Xin, Xin & Wang, Chaokun & Ying, Xiang & Wang, Boyang, 2017. "Deep community detection in topologically incomplete networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 342-352.
    • Handle: RePEc:eee:phsmap:v:469:y:2017:i:c:p:342-352
    DOI: 10.1016/j.physa.2016.11.029
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    References listed on IDEAS

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    1. Sun, Peng Gang, 2015. "Community detection by fuzzy clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 408-416.
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    Cited by:

    1. Dongming Chen & Mingshuo Nie & Fei Xie & Dongqi Wang & Huilin Chen, 2024. "Link Prediction and Graph Structure Estimation for Community Detection," Mathematics, MDPI, vol. 12(8), pages 1-16, April.

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