AGGLOMERATIVE CLUSTERING BASED ON LABEL PROPAGATION FOR DETECTING OVERLAPPING AND HIERARCHICAL COMMUNITIES IN COMPLEX NETWORKS

Yuxin Zhao (), Shenghong Li () and Shilin Wang ()
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Yuxin Zhao: Department of Electronic Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, P. R. China
Shenghong Li: Department of Electronic Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, P. R. China
Shilin Wang: School of Information Security Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, P. R. China

Advances in Complex Systems (ACS), 2014, vol. 17, issue 06, 1-22

Abstract: Community detection is an important issue to understand the structural and functional properties of complex networks, which still remains a challenging subject. In some complex networks, a node may belong to multiple communities, implying overlapping community structure. Moreover, complex networks often show a hierarchical structure where small communities group together to form larger ones. In this paper, we propose a novel parameter-free algorithm called agglomerative clustering based on label propagation algorithm (ACLPA) to detect both overlapping and hierarchical community structure in complex networks. By combining the advantages of agglomerative clustering and label propagation, our algorithm can build the hierarchical tree of overlapping communities in large-scale networks. The tests on both synthetic and real-world networks give excellent results and demonstrate the effectiveness and efficiency of our algorithm.

Keywords: Complex network; overlapping communities; hierarchical structure; agglomerative clustering; label propagation (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219525914500210

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