Detecting temporal community from dynamic heterogeneous networks

Abstract

Heterogeneous networks have become an important model to represent complex network. However, many existing community detection methods for dynamic network are hardly applied in heterogeneous networks. In this paper, we present a multi-view learning based algorithm for dynamic heterogeneous networks, which treats network individually, combines heterogeneous information and improves the quality. Compared with the traditional methods, experimental results on real network show that our proposed algorithm can detect the community structure in dynamic heterogeneous networks.