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Using minimum matching for clustering with balancing constraints

Clustering is a major task in data mining which is used in many applications. However, general clustering is inappropriate for many applications where some constraints should be applied. One category of these constraints is the cluster size constraint. In this paper, we propose a new algorithm for solving the clustering with balancing constraints by using the minimum matching. We compare our algorithm with the method proposed by Banerjee and Ghosh that uses stable matching and show that our algorithm converge to the final solution in fewer iterations.