Finding redundant and complementary communities in multidimensional networks

Michele Berlingerio, Michele Coscia, Fosca Giannotti

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Abstract

Community Discovery in networks is the problem of detecting, for each node, its membership to one of more groups of nodes, the communities, that are densely connected, or highly interactive. We define the community discovery problem in multidimensional networks, where more than one connection may reside between any two nodes. We also introduce two measures able to characterize the communities found. Our experiments on real world multidimensional networks support the methodology proposed in this paper, and open the way for a new class of algorithms, aimed at capturing the multifaceted complexity of connections among nodes in a network.

Original languageEnglish
Title of host publicationCIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management
Pages2181-2184
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: 24 Oct 201128 Oct 2011

Conference

Conference20th ACM Conference on Information and Knowledge Management, CIKM'11
CountryUnited Kingdom
CityGlasgow
Period24/10/1128/10/11

Keywords

  • community discovery
  • multidimensional network analysis

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