Identification and Evaluation of Weak Community Structures in Networks

Identifying intrinsic structures in large networks is a fundamental problem in many fields, such as engineering, social science and biology. In this paper, we are concerned with communities, which are densely connected sub-graphs in a network, and address two critical issues for finding community structures from large experimental data. First, most existing network clustering methods assume sparse networks and networks with strong community structures. In contrast, we consider sparse and dense networks with weak community structures. We introduce a set of simple operations that capture local neighborhood information of a node to identify weak communities. Second, we consider the issue of automatically determining the most appropriate number of communities, a crucial problem for all clustering methods. This requires to properly evaluate the quality of community structures. Built atop a function for network cluster evaluation by Newman and Girvan, we extend their work to weighted graphs...

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Jianhua Ruan, Weixiong Zhang
• Keywords: AAAI 2006, Community Structures, Intelligent Agents, Strong Community Structures, Weak Community Structures