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Detecting communities by the core-vertex and intimate degree in complex networks

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  • Wang, Xingyuan
  • Li, Junqiu

Abstract

In this paper, we present a new approach to extract communities in the complex networks with considerable accuracy. We introduce the core-vertex and the intimate degree between the community and its neighboring vertices. First, we find the core-vertices as the initial community. These core-vertices are then expanded using intimate degree function during extracting community structure from the given network. In addition, our algorithm successfully finds common nodes between communities. Experimental results using some real-world networks data shows that the performance of our algorithm is satisfactory.

Suggested Citation

  • Wang, Xingyuan & Li, Junqiu, 2013. "Detecting communities by the core-vertex and intimate degree in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2555-2563.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:10:p:2555-2563
    DOI: 10.1016/j.physa.2013.01.039
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    References listed on IDEAS

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    1. Chen, Duanbing & Fu, Yan & Shang, Mingsheng, 2009. "A fast and efficient heuristic algorithm for detecting community structures in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(13), pages 2741-2749.
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    Cited by:

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    11. Shang, Ronghua & Luo, Shuang & Li, Yangyang & Jiao, Licheng & Stolkin, Rustam, 2015. "Large-scale community detection based on node membership grade and sub-communities integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 279-294.
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