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Overlapping community detection using neighborhood ratio matrix

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dc.creator Eustace, Justine
dc.creator Wang, Xingyuan
dc.creator Cui, Yaozu
dc.date 2021-05-05T09:38:51Z
dc.date 2021-05-05T09:38:51Z
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). Overlapping community detection using neighborhood ratio matrix. Physica A: Statistical Mechanics and its Applications, 421, 510-521.
dc.identifier http://dx.doi.org/10.1016/j.physa.2014.11.039
dc.identifier http://hdl.handle.net/20.500.12661/2945
dc.identifier.uri http://hdl.handle.net/20.500.12661/2945
dc.description Abstract. Full text article available at https://doi.org/10.1016/j.physa.2014.11.039
dc.description The participation of a node in more than one community is a common phenomenon in complex networks. However most existing methods, fail to identify nodes with multiple community affiliation, correctly. In this paper, a unique method to define overlapping community in complex networks is proposed, using the overlapping neighborhood ratio to represent relations between nodes. Matrix factorization is then utilized to assign nodes into their corresponding community structures. Moreover, the proposed method demonstrates the use of Perron clusters to estimate the number of overlapping communities in a network. Experimental results in real and artificial networks show, with great accuracy, that the proposed method succeeds to recover most of the overlapping communities existing in the network.
dc.language en
dc.publisher Elsevier
dc.subject Complex networks
dc.subject Nodes
dc.subject Overlapping community
dc.subject Perron clusters
dc.subject Network
dc.subject Neighboring ratio
dc.subject Data mining
dc.subject Overlapping neighborhood ratio
dc.subject Neighborhood ratio matrix
dc.subject Ratio matrix
dc.subject Matrix factorization
dc.subject Perron clusters
dc.title Overlapping community detection using neighborhood ratio matrix
dc.type Article


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