We consider the problem of correlation clustering on graphs with constraints
on both the cluster sizes and the positive and negative weights of edges. Our
contributions are twofold: First, we introduce the problem of correlation
clustering with bounded cluster sizes...
Second, we extend the regime of weight
values for which the clustering may be performed with constant approximation
guarantees in polynomial time and apply the results to the bounded cluster size