Depot Institutionnel de l'UMBB >
Publications Scientifiques >
Publications Internationales >
Veuillez utiliser cette adresse pour citer ce document :
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/7333
|
Titre: | A new model for communities' detection in dynamic social networks inspired from human families |
Auteur(s): | Djerbi, Rachid Amad, Mourad Imache, Rabah |
Mots-clés: | Dynamic social networks Community detection Communities overlap Large families Guality of community structures Stability |
Date de publication: | 2020 |
Editeur: | Inderscience |
Collection/Numéro: | International Journal of Internet Technology and Secured Transactions / Vol. 10, N°1/2 (2020),;pp.24 - 60 |
Résumé: | Nowadays, social networks have been widely used by different people for different purposes in the world. The discovering of communities is a widespread subject in the space of social networks analysis. Many interesting solutions have been proposed in the literature. However, most solutions have common problems: the stability and the community structures quality. In this paper, we propose a new model to find communities based on a new concept called 'large families'. This model will be used, to motivate a community detection strategy to identify and effectively monitor the evolution of dynamic communities. We propose a compromise between the stability and the quality metrics. We apply our model on a real social network of the karate club of Zachary. Also, we describe experiences of our model on a large scale network of Enron's email data set as broader Benchmark Network. Simulations results show that our proposed model is globally satisfactory. |
URI/URL: | http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/7333 |
Collection(s) : | Publications Internationales
|
Fichier(s) constituant ce document :
|
Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.
|