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Towards Online Multiresolution Community Detection in Large-Scale Networks

The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on...

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Detalles Bibliográficos
Autores principales: Huang, Jianbin, Sun, Heli, Liu, Yaguang, Song, Qinbao, Weninger, Tim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3161084/
https://www.ncbi.nlm.nih.gov/pubmed/21887325
http://dx.doi.org/10.1371/journal.pone.0023829
Descripción
Sumario:The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks.