期刊
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
卷 374, 期 1, 页码 483-490出版社
ELSEVIER
DOI: 10.1016/j.physa.2006.07.023
关键词
overlapping community structure; modular function; spectral mapping; fuzzy c-means clustering; complex network
Identification of (overlapping) communities/clusters in a complex network is a general problem in data mining of network data sets. In this paper, we devise a novel algorithm to identify overlapping communities in complex networks by the combination of a new modularity function based on generalizing NG's Q function, an approximation mapping of network nodes into Euclidean space and fuzzy c-means clustering. Experimental results indicate that the new algorithm is efficient at detecting both good clusterings and the appropriate number of clusters. (c) 2006 Elsevier B.V. All rights reserved.
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