A non-dominated neighbor immune algorithm for community detection in networks
Proceedings of the 13th annual conference on Genetic and evolutionary computation
On selection of objective functions in multi-objective community detection
Proceedings of the 20th ACM international conference on Information and knowledge management
Multi-objective community detection in complex networks
Applied Soft Computing
A multiobjective hybrid evolutionary algorithm for clustering in social networks
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
A posteriori approach for community detection
Journal of Computer Science and Technology - Special issue on Community Analysis and Information Recommendation
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Community Detection in Complex Networks: Multi-objective Enhanced Firefly Algorithm
Knowledge-Based Systems
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A multiobjective genetic algorithm to uncover community structure in complex network is proposed. The algorithm optimizes two objective functions able to identify densely connected groups of nodes having sparse interconnections. The method generates a set of network divisions at different hierarchical levels in which solutions at deeper levels, consisting of a higher number of modules, are contained in solutions having a lower number of communities. The number of modules is automatically determined by the better tradeoff values of the objective functions. Experiments on synthetic and real life networks show the capability of the method to successfully detect the network structure.