Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/53671
Title: Detecting hierarchical and overlapping community structures in networks
Authors: Ganganath, N
Chen, GR
Cheng, CT 
Issue Date: 2014
Publisher: IEICE
Source: Proceedings of NOLTA 2014 : 2014 International Symposium on Nonlinear Theory and its Applications, September 14-18, 2014, Luzern, Switzerland, p. 345-348 How to cite?
Abstract: Community structure can be observed in many natural, biological and social networks. Studies suggest that these communities may have organized in a hierarchical manner while some communities overlap with others. This paper introduces an algorithm to detect such hierarchical and overlapping community structures in networks based on the concept of maximal cliques. It introduces an alternate modularity for evaluating overlapping community structures. Unlike existing algorithms for detecting hierarchical and overlapping community structures, the new algorithm is free of parameter tuning and random seeds. Experiments conducted on two real-world networks show that this algorithm is capable of providing satisfactory and consistent results.
URI: http://hdl.handle.net/10397/53671
Rights: © IEICE Japan 2014
The following publication N. Ganganath, G. Chen, and C.-T. Cheng, "Detecting hierarchical and overlapping community structures in networks," in Proceedings of NOLTA 2014 : 2014 International Symposium on Nonlinear Theory and its Applications, September 14-18, 2014, Luzern, Switzerland, IEICE, 2014, pp. 345-348 is published by IEICE and is available at http://www.ieice.org/~nolta/symposium/archive/2014/0ClickMe_NOLTA2014_Navi.pdf
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