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.
Type de document :
Article dans une revue
International Journal of Managing Information Technology (IJMIT), 2010, 2 (4), pp.1-9. <10.5121/ijmit.2010.2401>
Domaine :
Liste complète des métadonnées

https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00603165
Contributeur : Lylia Abrouk <>
Soumis le : vendredi 24 juin 2011 - 11:46:17
Dernière modification le : vendredi 24 juin 2011 - 13:41:55
Document(s) archivé(s) le : dimanche 25 septembre 2011 - 02:22:36

Fichier

IJIMIT-abrouk_gross_al_final.p...
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

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>

Partager

Métriques

Consultations de
la notice

192

Téléchargements du document

254