A dynamic community structure detection scheme based on social network incremental

被引：0
作者：
机构：
[1] National Digital Switching System Engineering and Technological R and D Center
来源：
Guo, J.-S. (52062011gjs@sina.com) | 1600年 / Science Press卷 / 35期
关键词：
Attribute weighted; Dynamic community; Incremental; Potential attraction; Social network;
D O I：
10.3724/SP.J.1146.2012.01590
中图分类号：
O144 [集合论]; O157 [组合数学（组合学）];
学科分类号：
070104 ;
摘要：
In the real world, the structure of social networks is not static, but varying with time's changing, and the same communities as an essential feature of social networks is also true. An incremental dynamic community detecting algorithm is proposed to reveal the actual communities based attribute weighted networks. It associates attribute information with topology graph and defines topological potential attraction between nodes and communities, using the incremental comparing with previous time to update the current community structure. The experiment on real network data proved that the proposed algorithm could be more effectively and timely to discover meaningful community structure, and having a smaller time complexity.
引用
收藏
页码：2240 / 2246
页数：6
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