From local to global communities in large networks through consensus

Conference Paper

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.

Full Text

Duke Authors

Cited Authors

  • Tepper, M; Sapiro, G

Published Date

  • January 1, 2015

Published In

Volume / Issue

  • 9423 /

Start / End Page

  • 659 - 666

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 13 (ISBN-13)

  • 9783319257501

Digital Object Identifier (DOI)

  • 10.1007/978-3-319-25751-8_79

Citation Source

  • Scopus