A novel visual clustering algorithm for finding community in complex network

Authors:
Shuzhong Yang;Siwei Luo;Jianyu Li
Affiliations:
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;School of Computer and Software, Communication University of China, Beijing, China
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

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Abstract

Complex network is an active research field in complex system in recent years. In this paper, we investigate the topological structure of complex networks and present a novel unsupervised visual clustering algorithm for finding community in complex networks. We firstly introduce a new distance between nodes to measure the dissimilarity between nodes and obtain the distance matrix. Then the rows (columns) of distance matrix are reordered according to the dissimilarity and the reordered matrix is displayed as an intensity image. Clusters are indicated by dark blocks of pixels along the main diagonal. The experiments show that our algorithm has good performance and can find the community structure hidden in complex networks.