DocumentCode :
2409780
Title :
Evaluating Community Structure in Bipartite Networks
Author :
Liu, Xin ; Murata, Tsuyoshi
Author_Institution :
Dept. of Comput. Sci., Tokyo Inst. of Technol., Tokyo, Japan
fYear :
2010
fDate :
20-22 Aug. 2010
Firstpage :
576
Lastpage :
581
Abstract :
Communities in unipartite networks are often understood as groups of nodes within which links are dense but between which links are sparse. Such communities are not suited to bipartite networks, as there is only one-to-one correspondence between communities of different types. Recently, B. Long et al. Introduced the link-pattern based community, which allows many-to-many correspondence between communities. In this paper, we propose a measure for evaluating the goodness of different partitions of a bipartite network into link-pattern based communities. Such a measure is useful for both comparing various community detection methods and devising new community detection algorithm based on optimization. We demonstrate the effectiveness of the proposed measure using the famous Southern women bipartite network.
Keywords :
Internet; complex networks; Southern women bipartite network; community structure evaluation; link-pattern based community; many-to-many correspondence; unipartite networks; Biology; Communities; Computer science; Conferences; Joining processes; Optimization; Partitioning algorithms; bipartite network; community structure; link mining; modularity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Social Computing (SocialCom), 2010 IEEE Second International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-8439-3
Electronic_ISBN :
978-0-7695-4211-9
Type :
conf
DOI :
10.1109/SocialCom.2010.91
Filename :
5591355
Link To Document :
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