Overlapping community detection using neighborhood ratio matrix

Simple item page
dc.contributor.authorEustace, Justine
dc.contributor.authorWang, Xingyuan
dc.contributor.authorCui, Yaozu
dc.date.accessioned2021-05-05T09:38:51Z
dc.date.available2021-05-05T09:38:51Z
dc.date.issued2015
dc.descriptionAbstract. Full text article available at https://doi.org/10.1016/j.physa.2014.11.039en_US
dc.description.abstractThe 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.en_US
dc.identifier.citationEustace, J., Wang, X., & Cui, Y. (2015). Overlapping community detection using neighborhood ratio matrix. Physica A: Statistical Mechanics and its Applications, 421, 510-521.en_US
dc.identifier.issnhttp://dx.doi.org/10.1016/j.physa.2014.11.039
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2945
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectComplex networksen_US
dc.subjectNodesen_US
dc.subjectOverlapping communityen_US
dc.subjectPerron clustersen_US
dc.subjectNetworken_US
dc.subjectNeighboring ratioen_US
dc.subjectData miningen_US
dc.subjectOverlapping neighborhood ratioen_US
dc.subjectNeighborhood ratio matrixen_US
dc.subjectRatio matrixen_US
dc.subjectMatrix factorizationen_US
dc.subjectPerron clustersen_US
dc.titleOverlapping community detection using neighborhood ratio matrixen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Eustace, Wang and Yaozu.pdf
Size:
82.75 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Journal Articles