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Discovering communities in complex networks by edge label propagation

The discovery of the community structure of real-world networks is still an open problem. Many methods have been proposed to shed light on this problem, and most of these have focused on discovering node community. However, link community is also a powerful framework for discovering overlapping comm...

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Detalles Bibliográficos
Autores principales: Liu, Wei, Jiang, Xingpeng, Pellegrini, Matteo, Wang, Xiaofan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772381/
https://www.ncbi.nlm.nih.gov/pubmed/26926830
http://dx.doi.org/10.1038/srep22470
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author Liu, Wei
Jiang, Xingpeng
Pellegrini, Matteo
Wang, Xiaofan
author_facet Liu, Wei
Jiang, Xingpeng
Pellegrini, Matteo
Wang, Xiaofan
author_sort Liu, Wei
collection PubMed
description The discovery of the community structure of real-world networks is still an open problem. Many methods have been proposed to shed light on this problem, and most of these have focused on discovering node community. However, link community is also a powerful framework for discovering overlapping communities. Here we present a novel edge label propagation algorithm (ELPA), which combines the natural advantage of link communities with the efficiency of the label propagation algorithm (LPA). ELPA can discover both link communities and node communities. We evaluated ELPA on both synthetic and real-world networks, and compared it with five state-of-the-art methods. The results demonstrate that ELPA performs competitively with other algorithms.
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spelling pubmed-47723812016-03-07 Discovering communities in complex networks by edge label propagation Liu, Wei Jiang, Xingpeng Pellegrini, Matteo Wang, Xiaofan Sci Rep Article The discovery of the community structure of real-world networks is still an open problem. Many methods have been proposed to shed light on this problem, and most of these have focused on discovering node community. However, link community is also a powerful framework for discovering overlapping communities. Here we present a novel edge label propagation algorithm (ELPA), which combines the natural advantage of link communities with the efficiency of the label propagation algorithm (LPA). ELPA can discover both link communities and node communities. We evaluated ELPA on both synthetic and real-world networks, and compared it with five state-of-the-art methods. The results demonstrate that ELPA performs competitively with other algorithms. Nature Publishing Group 2016-03-01 /pmc/articles/PMC4772381/ /pubmed/26926830 http://dx.doi.org/10.1038/srep22470 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Liu, Wei
Jiang, Xingpeng
Pellegrini, Matteo
Wang, Xiaofan
Discovering communities in complex networks by edge label propagation
title Discovering communities in complex networks by edge label propagation
title_full Discovering communities in complex networks by edge label propagation
title_fullStr Discovering communities in complex networks by edge label propagation
title_full_unstemmed Discovering communities in complex networks by edge label propagation
title_short Discovering communities in complex networks by edge label propagation
title_sort discovering communities in complex networks by edge label propagation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772381/
https://www.ncbi.nlm.nih.gov/pubmed/26926830
http://dx.doi.org/10.1038/srep22470
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