title: Towards online multiresolution community detection in large-scale networks.
abstract: 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.
authors: School of Software, Xidian University, Xi'an, China. jbhuang@xidian.edu.cn
authors: Jianbin
authors: J
authors: Huang
authors: Heli
authors: H
authors: Sun
authors: Yaguang
authors: Y
authors: Liu
authors: Qinbao
authors: Q
authors: Song
authors: Tim
authors: T
authors: Weninger
mesh_terms: D000465:Algorithms; D019058:Community Networks; D006801:Humans