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.
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Yang, S., Luo, S., Li, J. (2006). A Novel Visual Clustering Algorithm for Finding Community in Complex Network. In: Li, X., Zaïane, O.R., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2006. Lecture Notes in Computer Science(), vol 4093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811305_44
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DOI: https://doi.org/10.1007/11811305_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37025-3
Online ISBN: 978-3-540-37026-0
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