A Novel Community Detection Method Based on Rough Set K-Means

被引：5
|
作者：
Zhang Y. [1 ]
Wu B. [1 ]
Liu Y. [1 ]
机构：
[1] Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2017年 / 39卷 / 04期
关键词：
Community detection; K-Means; Rough set; Social network analysis;
D O I：
10.11999/JEIT160516
中图分类号：
学科分类号：
摘要：
Due to many community detection approaches regarding a community as one set of nodes which can not depict the vagueness of the community. A method based on rough set is proposed, it considers community as a lower and an upper approximation set which could depict the vagueness of the community. The method selects K nodes as the central nodes, then assembles iteratively nodes to their closest central nodes to form communities, and calculates subsequently a new central node in each community, around which to gather nodes again until convergence. Experimental results on public and synthetic networks verify the feasibility and effectiveness of the proposed method. © 2017, Science Press. All right reserved.
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收藏
页码：770 / 777
页数：7
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