Overlapping community detection using neighborhood ratio matrix

dc.creatorEustace, Justine
dc.creatorWang, Xingyuan
dc.creatorCui, Yaozu
dc.date2021-05-05T09:38:51Z
dc.date2021-05-05T09:38:51Z
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.2014.11.039
dc.descriptionThe 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.identifierEustace, J., Wang, X., & Cui, Y. (2015). Overlapping community detection using neighborhood ratio matrix. Physica A: Statistical Mechanics and its Applications, 421, 510-521.
dc.identifierhttp://dx.doi.org/10.1016/j.physa.2014.11.039
dc.identifierhttp://hdl.handle.net/20.500.12661/2945
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2945
dc.languageen
dc.publisherElsevier
dc.subjectComplex networks
dc.subjectNodes
dc.subjectOverlapping community
dc.subjectPerron clusters
dc.subjectNetwork
dc.subjectNeighboring ratio
dc.subjectData mining
dc.subjectOverlapping neighborhood ratio
dc.subjectNeighborhood ratio matrix
dc.subjectRatio matrix
dc.subjectMatrix factorization
dc.subjectPerron clusters
dc.titleOverlapping community detection using neighborhood ratio matrix
dc.typeArticle

Files