Pushing the envelope in overlapping communities detection

Said Jabbour, Nizar Mhadhbi, Badran Raddaoui, Lakhdar Sais

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

Abstract

Discovering the hidden community structure is a fundamental problem in network and graph analysis. Several approaches have been proposed to solve this challenging problem. Among them, detecting overlapping communities in a network is a usual way towards understanding the features of networks. In this paper, we propose a novel approach to identify overlapping communities in large complex networks. It makes an original use of a new community model, called k-clique-star, to discover densely connected structures in social interactions. We show that such model allows to ensure a minimum density on the discovered communities and overcomes some weaknesses of existing cohesive structures. Experimental results demonstrate the effectiveness and efficiency of our overlapping community model in a variety of real graphs.

Original languageEnglish
Title of host publicationAdvances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, Proceedings
EditorsArno Siebes, Wouter Duivesteijn, Antti Ukkonen
PublisherSpringer Verlag
Pages151-163
Number of pages13
ISBN (Print)9783030017675
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event17th International Symposium on Intelligent Data Analysis, IDA 2018 - ‘s-Hertogenbosch, Netherlands
Duration: 24 Oct 201826 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11191 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Symposium on Intelligent Data Analysis, IDA 2018
Country/TerritoryNetherlands
City‘s-Hertogenbosch
Period24/10/1826/10/18

Keywords

  • Community detection
  • Graph analysis
  • Overlapping community detection
  • Social networks

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