Multi-objective Overlapping Community Detection by Global and Local Approaches

  • Darian H. Grass-Boada
  • Airel Pérez-Suárez
  • Andrés Gago-Alonso
  • Rafael Bello
  • Alejandro Rosete
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10657)

Abstract

Overlapping community detection on social networks has received a lot of attention nowadays and it has been recently addressed as Multi-objective Optimization Evolutionary Algorithms. In this paper, we introduce a new algorithm, named MOGLAOC, which is based on the Pareto-dominance based MOEAs and combines global and local approaches for discovering overlapping communities. The experimental evaluation over four classical real-life networks showed that our proposal is promising and effective for overlapping community detection in social networks.

Keywords

Social network analysis Overlapping community detection Multi-objective Optimization Evolutionary Algorithm 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Darian H. Grass-Boada
    • 1
  • Airel Pérez-Suárez
    • 1
  • Andrés Gago-Alonso
    • 1
  • Rafael Bello
    • 2
  • Alejandro Rosete
    • 3
  1. 1.Advanced Technologies Application Center (CENATAV)HavanaCuba
  2. 2.Department of Computer ScienceUniversidad Central “Marta Abreu” de Las VillasSanta ClaraCuba
  3. 3.Facultad de Ingeniería InformáticaUniversidad Tecnológica de la Habana “José Antonio Echeverría” (CUJAE)HavanaCuba

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