Overlapping Community Detection by Local Decentralised Vertex-centred Process
February 13, 2017 Β· Declared Dead Β· π 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)
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Authors
MaΓ«l Canu, Marie-Jeanne Lesot, Adrien Revault d'Allonnes
arXiv ID
1702.03773
Category
cs.SI: Social & Info Networks
Cross-listed
cs.DM,
cs.DS
Citations
5
Venue
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)
Last Checked
3 months ago
Abstract
This paper focuses on the identification of overlapping communities, allowing nodes to simultaneously belong to several communities, in a decentralised way. To that aim it proposes LOCNeSs, an algorithm specially designed to run in a decentralised environment and to limit propagation, two essential characteristics to be applied in mobile networks. It is based on the exploitation of the preferential attachment mechanism in networks. Experimental results show that LOCNeSs is stable and achieves good overlapping vertex identification.
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