Overlapping Community Detection Using Multi-objective Approach and Rough Clustering

The detection of overlapping communities in Social Networks has been successfully applied in several contexts. Taking into account the high computational complexity of this problem as well as the drawbacks of single-objective approaches, community detection has been recently addressed as Multi-objective Optimization Evolutionary Algorithms (MOEAs). One of the challenges is to attain a final solution from the set of non-dominated solutions obtained by the MOEAs. In this paper, an algorithm to build a covering of the network based on the principles of the Rough Clustering is proposed. The experiments in a synthetic networks showed that our proposal is promising and effective for overlapping community detection in social networks.