Complex Network Topology Mining and Community Detection

Recently,various heterogeneous complex networks featured as “small-world” and “scale-free” have become a common research area of different disciplines. Especially, network topology mining and community detection have become focal topics. Through the investigations of typical features in complex networks, we propose a network nodes evaluation model based on a multivariate hierarchy method. With this model, network core nodes are extracted and a new algorithm about network topology reconstruction is put forward to implementing network backbone topology mining, which provides a new way for data mining and information retrieval. Furthermore, we propose two approaches for network community detection: broken edge clustering and center point diffusing. Experiments show that the methods presented in this paper are of high accuracy with good performance.