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A Novel Algorithm Infomap-SA of Detecting Communities in Complex Networks

Fang Hu1,2 and Yuhua Liu1
1.Schoolof Computer Science, Central China Normal University, Wuhan, 430079, China
2.College of Information Engineering, Hubei University of Chinese Medicine, Wuhan 430065, China

Abstract—Community detection is one of the most important issues in complex networks. In this paper, integrating Infomap and Simulated Annealing (SA) algorithm, and based on the thought of optimizationof the modularity function, the authors are proposing a novel algorithm Infomap-SA for detecting community. In order to verify the accuracy and efficiency of this algorithm, the performance of this algorithm is tested on several representative real-world networks and a set of computer-generated networks by LFR-benchmark. The experimental results show that this algorithm can identify the communities accurately and efficiently, and has higher values of modularity and density and lower computable complexity than Infomap algorithm. Furthermore, the Infomap-SA is more suitable for community detection of large-scale network.

Index Terms—Community detection; modularity; density; infomap-simulated annealing algorithm; simulation test

Cite: Fang Hu and Yuhua Liu, "A Novel Algorithm Infomap-SA of Detecting Communities in Complex Networks," Journal of Communications, vol. 10, no. 7, pp. 503-511, 2015. Doi: 10.12720/jcm.10.7.503-511