From local to global communities in large networks through consensus
Published
Conference Paper
© Springer International Publishing Switzerland 2015. 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