Finding Overlapping Communities Using Disjoint Community Detection Algorithms View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2009

AUTHORS

Steve Gregory

ABSTRACT

Many algorithms have been designed to discover community structure in networks. Most of these detect disjoint communities, while a few can find communities that overlap. We propose a new, two-phase, method of detecting overlapping communities. In the first phase, a network is transformed to a new one by splitting vertices, using the idea of split betweenness; in the second phase, the transformed network is processed by a disjoint community detection algorithm. This approach has the potential to convert any disjoint community detection algorithm into an overlapping community detection algorithm. Our experiments, using several “disjoint” algorithms, demonstrate that the method works, producing solutions, and execution times, that are often better than those produced by specialized “overlapping” algorithms. More... »

PAGES

47-61

References to SciGraph publications

  • 2005-06. Uncovering the overlapping community structure of complex networks in nature and society in NATURE
  • 1985-12. Comparing partitions in JOURNAL OF CLASSIFICATION
  • 2007. An Algorithm to Find Overlapping Community Structure in Networks in KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2007
  • 2008. A Fast Algorithm to Find Overlapping Communities in Networks in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
  • 2004-03. Detecting community structure in networks in THE EUROPEAN PHYSICAL JOURNAL B
  • 2008-05. Hierarchical structure and the prediction of missing links in networks in NATURE
  • 2005. Efficient Identification of Overlapping Communities in INTELLIGENCE AND SECURITY INFORMATICS
  • Book

    TITLE

    Complex Networks

    ISBN

    978-3-642-01205-1
    978-3-642-01206-8

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-01206-8_5

    DOI

    http://dx.doi.org/10.1007/978-3-642-01206-8_5

    DIMENSIONS

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