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Community Detection by an Efficient Ant Colony Approach

  • Lúcio Pereira de Andrade
  • Rogério Pinto Espíndola
  • Nelson Francisco Favilla Ebecken
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8502)

Abstract

Community detection is an efficient tool to analyze large complex networks offering new insights about their structures and functioning. A community is a significant organizational unity formed by nodes with more connections between them. Ant colony algorithms have been used to detect communities on a fast and efficient way. In this work, changes are performed on an ant colony algorithm for community detection by means of modularity optimization. The changes rely on the way an ant moves and on the adopted stopping criteria. To assess the proposed strategy, benchmark networks are studied and preliminary results indicate that the suggested changes make the original algorithm more robust, reaching higher values of modularity of the detected communities.

Keywords

complex networks community detection ant colony optimization 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Lúcio Pereira de Andrade
    • 1
  • Rogério Pinto Espíndola
    • 2
  • Nelson Francisco Favilla Ebecken
    • 3
  1. 1.UFF, Federal Fluminense UniversityRio de JaneiroBrazil
  2. 2.UEZO, State University of West SideRio de JaneiroBrazil
  3. 3.UFRJ, Federal University of Rio de Janeiro (COPPE)Rio de JaneiroBrazil

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