基于覆盖最优划分的社团发现算法

doi:10.16451/j.cnki.issn1003-6059.201809006

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Abstract

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.

Key words： Cover Complex Network Community Detection Similarity

Received: 15 April 2018

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	Articles by authors
	YANG Xuejie
	CHEN Jie
	ZHAO Shu
	QIAN Feng
	ZHANG Yanping

Cite this article:

YANG Xuejie,CHEN Jie,ZHAO Shu等. Community Detection Algorithm Based on Optimal Partition of Covers[J]. , 2018, 31(9): 837-844.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201809006 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I9/837

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