A Hypergraph Model for Clustering Scale-free Network

Many complex networks possess the scale-free property, which makes the task of detecting communities from these networks difficult. The application of traditional clustering algorithms on these networks has not yielded a great deal of success. In this paper we present a method of detecting community structure based on hypergraph model to address this problem. The hypergraph model maps the relationship in the original data into a hypergraph. A hyperedge represents a relationship among subsets of data and the weight of the hyperedge reflects the strength of this affinity. We assign the density of a hyperedge to its weight. We present and illustrate the results of experiments on the Enron data set. The experiments demonstrate that our approach is applicable and effective.