From local to global communities in large networks through consensus

Mariano Tepper, Guillermo Sapiro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Given a universe of local communities of a large network, we aim at identifying the meaningful and consistent communities in it. We address this from a new perspective as the process of obtaining consensual community detections and formalize it as a bi-clustering problem. We obtain the global community structure of the given network without running expensive global community detection algorithms. The proposed mathematical characterization of the consensus problem and a new biclustering algorithm to solve it render the problem tractable for large networks. The approach is successfully validated in experiments with synthetic and large real-world networks, outperforming other state-ofthe-art alternatives in terms of speed and results quality.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAlvaro Pardo, Josef Kittler
PublisherSpringer Verlag
Pages659-666
Number of pages8
ISBN (Print)9783319257501
DOIs
StatePublished - 2015
Externally publishedYes
Event20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015 - Montevideo, Uruguay
Duration: Nov 9 2015Nov 12 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9423
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015
Country/TerritoryUruguay
CityMontevideo
Period11/9/1511/12/15

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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