Detecting the Overlapping and Hierarchical Community Structure in Networks

  • Hua-Wei Shen
Part of the Springer Theses book series (Springer Theses)


Empirical studies indicate that communities in real world networks are simultaneously overlapped and hierarchical. This implies that one node can participate in more than one community simultaneously and community further contains sub-communities. However, few methods are capable of simultaneously detecting the overlapping and hierarchical community structure in networks. In this chapter, taking maximal cliques as building blocks of community, a metric is proposed to quantify the overlapping community. With this metric, the overlapping community structure can be efficiently detected by directly finding the optimal partition of network using standard modularity. We also describe the applications on word association network and scientific collaboration network.


Maximal Clique Original Network Real World Network Optimal Cover Modularity Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hua-Wei Shen
    • 1
  1. 1.Institute of Computing TechnologyChinese Academy of SciencesBeijingChina

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