COMMUNITY DETECTION IN THE COLLABORATIVE WEB

COMMUNITY DETECTION IN THE COLLABORATIVE WEB 

Lylia Abrouk, David Gross-Amblard and Nadine Cullot LE2I, UMR CNRS 5158 University of Burgundy, Dijon, France 
lylia.abrouk@u-bourgogne.fr, david.gross-amblard@u-bourgogne.fr, nadine.cullot@u-bourgogne.fr 

ABSTRACT 

Most of the existing social network systems require from their users an explicit statement of their friendship relations. In this paper we focus on implicit Web communities and present an approach to automatically detect them, based on user’s resource manipulations. This approach is dynamic as user groups appear and evolve along with users interests over time. Moreover, new resources are dynamically labelled according to who is manipulating them. Our proposal relies on the fuzzy K-means clustering method and is assessed on large movie datasets. 

KEYWORDS 

Clustering, Data sharing, Information networks, user distance, Web community. 





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