Particle Competition and Cooperation for Uncovering Network Overlap Community Structure

  • Fabricio Breve
  • Liang Zhao
  • Marcos Quiles
  • Witold Pedrycz
  • Jiming Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6677)


Identification and classification of overlap nodes in communities is an important topic in data mining. In this paper, a new graph-based (network-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in the network to uncover overlap nodes, i.e., the algorithm can output continuous-valued output (soft labels), which corresponds to the levels of membership from the nodes to each of the communities. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.


Graph-based method community detection particle competition and cooperation overlap nodes 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fabricio Breve
    • 1
  • Liang Zhao
    • 1
  • Marcos Quiles
    • 2
  • Witold Pedrycz
    • 3
    • 4
  • Jiming Liu
    • 5
  1. 1.Department of Computation, Institute of Mathematics and Computer ScienceUniversity of São PauloSão CarlosBrazil
  2. 2.Department of Science and TechnologyFederal University of São PauloSão José dos CamposBrazil
  3. 3.Department of Electrical and Computer EngineeringUniversity of AlbertaEdmontonCanada
  4. 4.Systems Research InstitutePolish Academy of SciencesWarsawPoland
  5. 5.Computer Science DepartmentHong Kong Baptist UniversityKowloonHong Kong

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