Overlapping community structure detection in networks

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Overlapping community structure detection in networks

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Conference on Information and Knowledge Management archive
Proceeding of the 17th ACM conference on Information and knowledge management table of contents

Napa Valley, California, USA

POSTER SESSION: Poster session 1/knowledge management table of contents

Pages 1371-1372

Year of Publication: 2008

ISBN:978-1-59593-991-3

Authors

Nan Du	Beijing University of Posts and Telecommunications, Beijing, China
Bai Wang	Beijing University of Posts and Telecommunications, Beijing, China
Bin Wu	Beijing University of Posts and Telecommunications, Beijing, China

Sponsors

ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval

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ACM New York, NY, USA

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ABSTRACT

Many systems in nature and human society take the form of networks with community structures. In this paper, we describe a simple algorithm COCD(Clique-based Overlapping Community Detection) to efficiently mine the overlapping communities in large-scale networks, which is useful for us to have a better understanding of the nested sub-structures embedded in the whole network.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Coen Bron , Joep Kerbosch, Algorithm 457: finding all cliques of an undirected graph, Communications of the ACM, v.16 n.9, p.575-577, Sept. 1973 [doi>10.1145/362342.362367]
	2	S. Fortunato and M. Barthelemy. Resolution limit in community detection. PNAS, 104(1):36--41, 2006.
	3	Nan Du , Bin Wu , Liutong Xu , Bai Wang , Xin Pei, A Parallel Algorithm for Enumerating All Maximal Cliques in Complex Network, Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops, p.320-324, December 18-22, 2006 [doi>10.1109/ICDMW.2006.17]
	4	Steve Gregory, An Algorithm to Find Overlapping Community Structure in Networks, Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases, September 17-21, 2007, Warsaw, Poland [doi>10.1007/978-3-540-74976-9_12]
	5	M. Newman. Detecting community structure in networks. The European Physical Journal B, 38(2):321--330, May 2004.
	6	M. Newman. Modularity and community structure in networks. PNAS, 103(23):8577--8582, 2006.
	7	G. Palla, I. Dernyi, and I. Farkas. Uncovering the overlapping community structure of complex network in nature and society. Nature, 435(7043):814--818, 2005.
	8	J. Pinney and D. Westhead. Betweenness-based decomposition methods for social and biological networks. Leeds University Press.
	9	http://www-personal.umich.edu/~mejn/netdata/