title: A novel complex networks clustering algorithm based on the core influence of nodes.
abstract: In complex networks, cluster structure, identified by the heterogeneity of nodes, has become a common and important topological property. Network clustering methods are thus significant for the study of complex networks. Currently, many typical clustering algorithms have some weakness like inaccuracy and slow convergence. In this paper, we propose a clustering algorithm by calculating the core influence of nodes. The clustering process is a simulation of the process of cluster formation in sociology. The algorithm detects the nodes with core influence through their betweenness centrality, and builds the cluster's core structure by discriminant functions. Next, the algorithm gets the final cluster structure after clustering the rest of the nodes in the network by optimizing method. Experiments on different datasets show that the clustering accuracy of this algorithm is superior to the classical clustering algorithm (Fast-Newman algorithm). It clusters faster and plays a positive role in revealing the real cluster structure of complex networks precisely.
authors.affiliation: School of Computer Science and Engineering, Beihang University, Beijing 100191, China ; School of Computer Science, McGill University, Montreal, QC, Canada H3A 0E9.
authors.forename: Chao
authors.identifier: 0000-0003-4414-4965
authors.initials: C
authors.lastname: Tong
authors.affiliation: School of Computer Science and Engineering, Beihang University, Beijing 100191, China.
authors.forename: Jianwei
authors.identifier: 0000-0003-3946-5107
authors.initials: J
authors.lastname: Niu
authors.affiliation: School of Computer Science and Engineering, Beihang University, Beijing 100191, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Dai
authors.affiliation: School of Computer Science and Engineering, Beihang University, Beijing 100191, China.
authors.forename: Zhongyu
authors.initials: Z
authors.lastname: Xie
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis
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