Detecting local community structures in complex networks based on local degree central nodes

被引:119
作者
Chen, Qiong [1 ]
Wu, Ting-Ting [1 ]
Fang, Ming [1 ]
机构
[1] S China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510640, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Complex networks; Local community detection; Local degree central node;
D O I
10.1016/j.physa.2012.09.012
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Detecting local communities in real-world graphs such as large social networks, web graphs, and biological networks has received a great deal of attention because obtaining complete information from a large network is still difficult and unrealistic nowadays. In this paper, we define the term local degree central node whose degree is greater than or equal to the degree of its neighbor nodes. A new method based on the local degree central node to detect the local community is proposed. In our method, the local community is not discovered from the given starting node, but from the local degree central node that is associated with the given starting node. Experiments show that the local central nodes are key nodes of communities in complex networks and the local communities detected by our method have high accuracy. Our algorithm can discover local communities accurately for more nodes and is an effective method to explore community structures of large networks. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:529 / 537
页数:9
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