Community Detection Algorithm Based on Optimal Partition of Covers
YANG Xuejie1,2, CHEN Jie1, ZHAO Shu1, QIAN Feng1,3, ZHANG Yanping1
1.School of Computer Science and Technology, Anhui University, Hefei 230601
2.School of Computer Science and Technology, Hefei Normal University, Hefei 230601
3.School of Mathematics and Computer Science, Tongling University, Tongling 244061
The overlapped region samples are divided through merging and dividing operation of sets based on the optimal partition concept, and thus the partition achieves minimal error. In this paper, the optimal partition of cover is introduced into the community detection, and a community detection algorithm based on optimal partition of covers(CDA_OPC) is proposed. The problem of community detection is converted to the optimal partition problem for the fixed coverage. In CDA_OPC, the covers can be constructed by utilizing the overlapped relationship between the nodes. Secondly, the optimal approximation of coverage is obtained through the merging and segmentation of covering subsets based on the concept of the optimal partition. Finally, the similarity between communities is calculated, and the multi-granularity community structure is finally formed through multi-level integration. Experimental results on real networks show that CDA _OPC is effective at community detection of networks.
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