Community detection using cooperative co-evolutionary differential evolution

Qiang Huang, Thomas White, Guanbo Jia, Mirco Musolesi, Nil Turan, Ke Tang, Shan He, John K. Heath, Xin Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)

Abstract

In many scientific fields, from biology to sociology, community detection in complex networks has become increasingly important. This paper, for the first time, introduces Cooperative Co-evolution framework for detecting communities in complex networks. A Bias Grouping scheme is proposed to dynamically decompose a complex network into smaller subnetworks to handle large-scale networks. We adopt Differential Evolution (DE) to optimize network modularity to search for an optimal partition of a network. We also design a novel mutation operator specifically for community detection. The resulting algorithm, Cooperative Co-evolutionary DE based Community Detection (CCDECD) is evaluated on 5 small to large scale real-world social and biological networks. Experimental results show that CCDECD has very competitive performance compared with other state-of-the-art community detection algorithms.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature, PPSN XII - 12th International Conference, Proceedings
Pages235-244
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2012
Event12th International Conference on Parallel Problem Solving from Nature, PPSN 2012 - Taormina, Italy
Duration: 1 Sep 20125 Sep 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7492 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Parallel Problem Solving from Nature, PPSN 2012
Country/TerritoryItaly
CityTaormina
Period1/09/125/09/12

Bibliographical note

Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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