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Community detection in the collaborative Web

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 the user's resources 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 data sets.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00603165
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Submitted on : Friday, June 24, 2011 - 11:46:17 AM
Last modification on : Friday, July 17, 2020 - 2:53:54 PM
Long-term archiving on: : Sunday, September 25, 2011 - 2:22:36 AM

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Lylia Abrouk, David Gross-Amblard, Nadine Cullot. Community detection in the collaborative Web. International Journal of Managing Information Technology (IJMIT), 2010, 2 (4), pp.1-9. ⟨10.5121/ijmit.2010.2401⟩. ⟨hal-00603165⟩

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