A New Multimembership Clustering Method

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); PereiraLeal, Enright and Ouzounis, (Bioinformatics, 2004); Futschik and Carlisle, (J. Bioinformatics and Computational Biology 2005))