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Community detection using local neighborhood in complex networks

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dc.creator Eustace, Justine
dc.creator Wang, Xingyuan
dc.creator Cui, Yaozu
dc.date 2021-05-05T08:13:52Z
dc.date 2021-05-05T08:13:52Z
dc.date 2015
dc.date.accessioned 2022-10-20T13:47:42Z
dc.date.available 2022-10-20T13:47:42Z
dc.identifier Eustace, J., Wang, X., & Cui, Y. (2015). Community detection using local neighborhood in complex networks. Physica A: Statistical Mechanics and its Applications, 436, 665-677.
dc.identifier DOI: 10.1016/j.physa.2015.05.044
dc.identifier http://hdl.handle.net/20.500.12661/2939
dc.identifier.uri http://hdl.handle.net/20.500.12661/2939
dc.description Abstract. Full text article available at https://doi.org/10.1016/j.physa.2015.05.044
dc.description It is common to characterize community structure in complex networks using local neighborhood. Existing related methods fail to estimate the accurate number of nodes present in each community in the network. In this paper a community detection algorithm using local community neighborhood ratio function is proposed. The proposed algorithm predicts vertex association to a specific community using visited node overlapped neighbors. In the beginning, the algorithm detects local communities; then through iterations and local neighborhood ratio function, final communities are detected by merging close related local communities. Analysis of simulation results on real and artificial networks shows the proposed algorithm detects well defined communities in both networks by wide margin.
dc.language en
dc.publisher Elsevier
dc.subject Complex networks
dc.subject Local neighborhood
dc.subject Neighborhood ratio
dc.subject Community detection algorithms
dc.subject Local community neighborhood
dc.subject Data mining
dc.subject Behavior science
dc.subject Community structure
dc.subject Algorithms
dc.title Community detection using local neighborhood in complex networks
dc.type Article


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