Multi-objective Approach for Local Community Computation

In this paper we propose a new approach for efficiently identifying local communities in complex networks. Most existing approaches are based on applying a greedy optimization process guided by a given objective function. Different objective functions have been proposed in the scientific literature, each capturing some specific feature of desired communities. In this work, we propose exploring a new multi-objective approach that allows combining different objective functions. First results obtained from experiments on benchmark networks argue for the relevancy of our approach.