Volume 4, Issue 2, March 2016, Pages: 13-18
Received: Apr. 15, 2016;
Published: Apr. 16, 2016
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Jialin He, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
Duanbing Chen, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
Chongjing Sun, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
Community structure is one of important characteristics in complex networks and contributes to the understanding of function in corresponding complex systems. Many methods based on modularity optimization have been proposed in the past few years. To obtain a good community partition, they must maximize the modularity from scratch, which have low efficiency. In this paper, we suggest a novel method which first constructs a small network according to connection strength index and then uses Blondel method to detect communities. Experimental results on real and synthetic networks show that compared with the traditional method our method can not only maintain the quality of communities but also improve the efficiency greatly.
A Fast Method for Community Detection Based on Compressing Networks, Software Engineering.
Vol. 4, No. 2,
2016, pp. 13-18.
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