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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))