Detecting overlapping communities by seed community in weighted complex networks

Simple item page
dc.contributor.authorLi, Junqiu
dc.contributor.authorWang, Xingyuan
dc.contributor.authorEustace, Justine
dc.date.accessioned2020-11-24T14:24:08Z
dc.date.available2020-11-24T14:24:08Z
dc.date.issued2013
dc.descriptionAbstract. Full text article available at https://doi.org/10.1016/j.physa.2013.07.066en_US
dc.description.abstractDetection of community structures in the weighted complex networks is significant to understand the network structures and analysis of the network properties. We present a unique algorithm to detect overlapping communities in the weighted complex networks with considerable accuracy. For a given weighted network, all the seed communities are first extracted. Then to each seed community, more community members are absorbed using the absorbing degree function. In addition, our algorithm successfully finds common nodes between communities. The experiments using some real-world networks show that the performance of our algorithm is satisfactory.en_US
dc.identifier.citationLi, J., Wang, X., & Eustace, J. (2013). Detecting overlapping communities by seed community in weighted complex networks. Physica A: Statistical Mechanics and its Applications, 392(23), 6125-6134.en_US
dc.identifier.otherDOI:10.1016/j.physa.2013.07.066
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2595
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectSeed communityen_US
dc.subjectWeighted networksen_US
dc.subjectOverlapping communityen_US
dc.subjectAbsorbing degreeen_US
dc.subjectCommunity structuresen_US
dc.subjectCommon nodesen_US
dc.subjectCommunityen_US
dc.subjectNetworken_US
dc.subjectComplex networksen_US
dc.titleDetecting overlapping communities by seed community in weighted complex networksen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Li.pdf
Size:
4.78 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