Algorithm for detecting overlapping community in complex networks

被引：0

作者：

机构：

[1] Jilin University

[2] School of Computer Science and Information Technology, Northeast Normal University

来源：

Li, Y. (lywen1024@163.com) | 1600年 / Binary Information Press, Flat F 8th Floor, Block 3, Tanner Garden, 18 Tanner Road, Hong Kong卷 / 10期

关键词：

Clustering algorithm; Complex networks; Detecting community; Overlapping community;

D O I：

10.12733/jics20101804

中图分类号：

学科分类号：

摘要：

Detecting communities from complex networks has been the focus of many recent efforts on complex networks. In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. We introduce a new algorithm for overlapping community finding, the algorithm first finds some seeds and expands these seeds into a community. We perform the algorithm on different data to demonstrate that performance of our algorithm is robust across diverse parameters. The algorithm is compared with current representative algorithms in community mining. Experimental results show the feasibility and validity of our algorithm. We show that our algorithm is highly effective at discovering community structure in different types of complex networks. Copyright © 2013 Binary Information Press.

引用

页码：2625 / 2632

页数：7

共 18 条

[1]

He D., Zhou X., Wang Z., Et al., Community mining in complex networks clustering combination based genetic algorithm, Acta Automatica Sinica, 36, 8, pp. 1160-1170, (2010)

[2]

Lou F., Yang Y., Chen C.F., Et al., Modular organization of protein interaction networks, Bioinformatics, 23, 2, pp. 207-214, (2007)

[3]

Brohee S., Van Helden J., Et al., Evaluation of clustering algorithms for protein-protein interaction networks, BMC Bioinformatics, 7, (2006)

[4]

Wasserman S., Faust K., Social network analysis: Methods and applications, Structural Analysis in the Social Sciences, (1994)

[5]

Broder A., Kumar R., Et al., Graphstructure in the web, Computer Networks, 33, pp. 309-320, (2000)

[6]

Newman M.E.J., The structure of scientific collaboration networks, Proc. Natl. Acad. Sci. USA, 98, 2, pp. 404-409, (2001)

[7]

Camacho J., Guimera R., Amaral L.A.N., Robust patterns in food web structure, Phys. Rev. Lett., 88, (2002)

[8]

Porter M.A., Onnela J.P., Mucha P.J., Communities in networks, Notices of the American Mathematical Society, 56, 9, pp. 1082-1097, (2009)

[9]

Ahn Y.Y., Bagro J.P., Lehmann S., Link communities reveal multiscale complexity in networks, Nature, 466, pp. 761-764, (2010)

[10]

Newman M.E.J., Girvan M., Finding and evaluating community structure in networks, Phys. Rev. E, 69, (2004)

← 1 2 →