Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 405, Issue -, Pages 85-91Publisher
ELSEVIER
DOI: 10.1016/j.physa.2014.03.027
Keywords
Complex network; Community structures; Maximal sub-graph; Clustering coefficient
Categories
Funding
- National Natural Science Foundation of China [61370145, 61173183, 60973152]
- Doctoral Program Foundation of Institution of Higher Education of China [20070141014]
- Program for Liaoning Excellent Talents in University [LR2012003]
- National Natural Science Foundation of Liaoning province [20082165]
- Fundamental Research Funds for the Central Universities [DUT12JB06]
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In this paper, we present an alternate algorithm for detecting overlapping community structures in the complex network. Two concepts named the maximal sub-graph and the clustering coefficient between two neighboring communities are introduced. First, all the maximal sub-graphs are extracted from the original networks and then merge them by considering the clustering coefficient of two neighboring maximal sub-graphs. And a new extended modularity is proposed to quantify this algorithm. The other advantage of this algorithm is that the overlapping vertex can be detected. The effectiveness of our algorithm is tested on some real networks. Finally, we compare the computational complexity of this algorithm with selected close related algorithms. The results show that this algorithm gives satisfactory results. (C) 2014 Elsevier B.V. All rights reserved.
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