A Divisive Hierarchical Structural Clustering Algorithm for Networks

Many systems in sciences, engineering and nature can be modeled as networks. Examples are internet, metabolic networks and social networks. Network clustering algorithms aimed to find hidden structures from networks are important to make sense of complex networked data. In this paper we present a new clustering method for networks. The proposed algorithm can find hierarchical structure of clusters without requiring any input parameters. The experiments using real data demonstrate an outstanding performance of the new method.

• Type: Conference
• Year: 2007
• Where: ICDM
• Authors: Nurcan Yuruk, Mutlu Mete, Xiaowei Xu, Thomas A. J. Schweiger
• Keywords: Data Mining, ICDM 2007, Metabolic Networks, Network Clustering Algorithms, Social Networks