Community detection in scale-free networks based on hypergraph model

Authors:
Rong Qian;Wei Zhang;Bingru Yang
Affiliations:
School of Information Engineering, University of Science and Technology Beijing, Beijing, China;School of Information Engineering, University of Science and Technology Beijing, Beijing, China;School of Information Engineering, University of Science and Technology Beijing, Beijing, China
Venue:
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Year:
2007

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Abstract

The investigation of community structures in networks is an important issue in many domains and disciplines. There have been considerable recent interest algorithms for finding communities in networks. In this paper we present a method of detecting community structure based on hypergraph model. 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. These experiments demonstrate that our approach is applicable and effective.