Community detection using local neighborhood in complex networks

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dc.creatorEustace, Justine
dc.creatorWang, Xingyuan
dc.creatorCui, Yaozu
dc.date2021-05-05T08:13:52Z
dc.date2021-05-05T08:13:52Z
dc.date2015
dc.date.accessioned2022-10-20T13:47:42Z
dc.date.available2022-10-20T13:47:42Z
dc.descriptionAbstract. Full text article available at https://doi.org/10.1016/j.physa.2015.05.044
dc.descriptionIt 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.identifierEustace, 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.identifierDOI: 10.1016/j.physa.2015.05.044
dc.identifierhttp://hdl.handle.net/20.500.12661/2939
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2939
dc.languageen
dc.publisherElsevier
dc.subjectComplex networks
dc.subjectLocal neighborhood
dc.subjectNeighborhood ratio
dc.subjectCommunity detection algorithms
dc.subjectLocal community neighborhood
dc.subjectData mining
dc.subjectBehavior science
dc.subjectCommunity structure
dc.subjectAlgorithms
dc.titleCommunity detection using local neighborhood in complex networks
dc.typeArticle

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