A Community Extraction Method using Intersection Graph and Semantic Analysis in Complex Network

Abstract

There is an increasing number of researches of complex networks such as World Wide Web, social networks and biological networks. They have found the property of a scale free, a small world, a large clustering coefficient, and so on. One of the hot topics in this area is community detection. Nodes belonging to a community are likely to have common properties. For instance, in the World Wide Web, a community may be a set of pages which belong to a same topic. Community structure is undoubtedly a key characteristic of complex networks. In this paper, we present a new framework for finding communities in complex networks and evaluate detecting the community. This framework uses the idea of intersection graph and uses semantic information such as text and attributes which appear in networks.