A two-phase strategy for detecting communities

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

One of the key objectives for representing real-world problems using networks is for detecting community structures. This is because detecting community structure is crucial for identifying the link between structure and function in complex networks, which is the key for solving many practical applications in various disciplines. The detection of "good" communities has proven to be a challenging task. This is due, mainly, to the fact that most current methods detect communities in independents. As a result, most of them do not work well on highly sparse networks. We propose in this paper a system called TPSDC that detects disjoint communities and works well on highly sparse networks. It does so by adopting the following procedure: (1) assigning a score to each vertex to reflect its relative importance to the whole network, (2) assigning a score to each link connecting two neighboring vertices to represent the degree of association between them, (3) employing a two-phase strategy for detecting disjoint communities, and (4) enhancing the density of community using a post-processing technique. We evaluated the quality of TPSDC by comparing it experimentally with nine methods. Results showed marked improvement.

Original languageBritish English
Title of host publicationProceedings of the International Conferences on ICT, Society, and Human Beings 2016, Web Based Communities and Social Media 2016, Big Data Analytics, Data Mining and Computational Intelligence 2016 and Theory and Practice in Modern Computing 2016 - Part of the Multi Conference on Computer Science and Information Systems 2016
EditorsLuis Rodrigues, Ajith P. Abraham, Jorg Roth, Piet Kommers
Pages113-120
Number of pages8
ISBN (Electronic)9789898533548
StatePublished - 2016
Event2017 International Conferences on Information and Communication Technology, Society, and Human Beings, ICT 2016, Web Based Communities and Social Media, WBC 2016, Big Data Analytics, Data Mining and Computational Intelligence, BIGDACI 2016 and Theory and Practice in Modern Computing, TPMC 2016 - Madeira, Portugal
Duration: 1 Jul 20164 Jul 2016

Publication series

NameProceedings of the International Conferences on ICT, Society, and Human Beings 2016, Web Based Communities and Social Media 2016, Big Data Analytics, Data Mining and Computational Intelligence 2016 and Theory and Practice in Modern Computing 2016 - Part of the Multi Conference on Computer Science and Information Systems 2016

Conference

Conference2017 International Conferences on Information and Communication Technology, Society, and Human Beings, ICT 2016, Web Based Communities and Social Media, WBC 2016, Big Data Analytics, Data Mining and Computational Intelligence, BIGDACI 2016 and Theory and Practice in Modern Computing, TPMC 2016
Country/TerritoryPortugal
CityMadeira
Period1/07/164/07/16

Keywords

  • Community detection
  • Community structure
  • Networks

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