Uncovering Overlapping Community Structure

  • Qinna Wang
  • Eric Fleury
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 116)

Abstract

Overlapping community structure has attracted much interest in recent years since Palla et al. proposed the k-clique percolation algorithm for community detection and pointed out that the overlapping community structure is more reasonable to capture the topology of networks. Despite many efforts to detect overlapping communities, the overlapping community problem is still a great challenge in complex networks. Here we introduce an approach to identify overlapping community structure based on an efficient partition algorithm. In our method, communities are formed by adding peripheral nodes to cores. Therefore, communities are allowed to overlap. We show experimental studies on synthetic networks to demonstrate that our method has excellent performances in community detection.

Keywords

Community Detection Normalize Mutual Information Strong Cluster Synthetic Network College Football 
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 2011

Authors and Affiliations

  • Qinna Wang
    • 1
  • Eric Fleury
    • 1
  1. 1.ENS de LyonLyonCedex 07

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