Abstract
The detection of 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); however, most of the algorithms following this approach only detect disjoint communities. In this paper, we extend the general Pareto-dominance based MOEAs framework for discovering overlapping communities. The experimental evaluation of our proposal over four real-life networks showed that it is effective for overlapping community detection.
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Grass-Boada, D.H., Pérez-Suárez, A., Bello, R., Rosete, A. (2018). Extending the Pareto-Dominance Based MOEAs Framework for Overlapping Community Detection. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Soft Computing. MICAI 2017. Lecture Notes in Computer Science(), vol 10632. Springer, Cham. https://doi.org/10.1007/978-3-030-02837-4_11
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DOI: https://doi.org/10.1007/978-3-030-02837-4_11
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