A new multimembership clustering method

Yongbin Ou; Cun-Quan Zhang

doi:10.3934/jimo.2007.3.619

Article Contents

2007, Volume 3, Issue 4: 619-624. Doi: 10.3934/jimo.2007.3.619

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A new multimembership clustering method

Yongbin Ou¹ and
Cun-Quan Zhang^1,

1.
Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310

Received: September 2006

Revised: April 2007

Published: October 2007

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Abstract

Clustering method is one of the most important tools in statistics. In a graph theory model, clustering is the process of finding all dense subgraphs. In this paper, a new clustering method is introduced. One of the most significant differences between the new method and other existing methods is that this new method constructs a much smaller hierarchical tree, which clearly highlights meaningful clusters. Another important feature of the new method is the feature of overlapping clustering or multi-membership. The property of multi-membership is a concept that has recently received increased attention in the literature (Palla, Derényi, Farkas and Vicsek, (Nature 2005); Pereira-Leal, Enright and Ouzounis, (Bioinformatics, 2004); Futschik and Carlisle, (J. Bioinformatics and Computational Biology 2005))

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Mathematics Subject Classification: 90C26, 90C46.

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