Volume 8 Number 11 (Nov. 2013)
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JSW 2013 Vol.8(11): 2930-2935 ISSN: 1796-217X
doi: 10.4304/jsw.8.11.2930-2935

Ant Colony Optimization for Detecting Communities from Bipartite Network

Yongcheng Xu1, Ling Chen1, Shengrong Zou2
1Department of Computer Science, Yangzhou University, Yangzhou, 225009, China
2State Key Lab of Novel Software Tech, Nanjing University, Nanjing, 210093, China

Abstract—In this paper, an algorithm based on ant colony optimization for community detection from bipartite networks is presented. The algorithm establishes a model graph for the ants’ searching. Each ant chooses its path according to the pheromone and heuristic information on each edge to construct a solution. Experimental results show that our algorithm can not only accurately identify the number of communities of a network, but also obtain higher quality of community detection.

Index Terms—Ant colony optimization, community detection, bipartite network.


Cite: Yongcheng Xu, Ling Chen and Shengrong Zou, "Ant Colony Optimization for Detecting Communities from Bipartite Network," Journal of Software vol. 8, no. 11, pp. 2930-2935, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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