Graph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members

Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible and clustering data is a useful tool for these data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members in each cluster. In this paper, we use hierarchical SVD to cluster graphs to desirable number of clusters and the number of members in each cluster. In this algorithm, users can select a range for the number of members in each cluster and the algorithm hierarchically cluster each clusters to achieve desirable range . The results show in hierarchical SVD algorithm, clustering measurement parameters are more desirable and clusters are as dense as possible. In this paper, simple and bipartite graphs are studied.