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Community Detection in Bipartite Network: A Modified Coarsening Approach

  • Alan ValejoEmail author
  • Vinícius Ferreira
  • Maria C. F. de Oliveira
  • Alneu de Andrade Lopes
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 795)

Abstract

Interest in algorithms for community detection in networked systems has increased over the last decade, mostly motivated by a search for scalable solutions capable of handling large-scale networks. Multilevel approaches provide a potential solution to scalability, as they reduce the cost of a community detection algorithm by applying it to a coarsened version of the original network. The solution obtained in the small-scale network is then projected back to the original large-scale model to obtain the desired solution. However, standard multilevel methods are not directly applicable to bipartite networks and there is a gap in existing literature on multilevel optimization applied to such networks. This article addresses this gap and introduces a novel multilevel method based on one-mode projection that allows executing traditional multilevel methods in bipartite network models. The approach has been validated with an algorithm for community detection that solves the Barber’s modularity problem. We show it can scale a target algorithm to handling larger networks, whilst preserving solution accuracy.

Notes

Acknowledgments

Author A. Valejo is supported by a scholarship from the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES). This work has been partially supported by the State of São Paulo Research Foundation (FAPESP) grants 17/05838-3; and the Brazilian Federal Research Council (CNPq) grants 302645/2015-2 and 3056-96/2013-0.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Alan Valejo
    • 1
    Email author
  • Vinícius Ferreira
    • 1
  • Maria C. F. de Oliveira
    • 1
  • Alneu de Andrade Lopes
    • 1
  1. 1.Institute of Mathematical and Computer Sciences (ICMC)University of São Paulo (USP)São CarlosBrazil

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