Séminaire Mathématique de Béjaia
Volume 16, Numéro 1, Pages 110-110
2018-12-31

A Social Recommender System With Privacy Preserving



Authors : Badis Lyes . Amad Mourad . Aïssani Djamil .

Abstract

P2P social networks are presented to give the users more control of their data and relations. This is due to the decentralized underlying architecture. Several architectures were proposed. They had proved the feasibility of implementing basic social networks features (eg. publish, share, comment …) on top of P2P architectures. Advanced features as social information retrieval and particularly the recommender systems are very hard to implement. This is due to the absence of a central server that has a complete view of the social graph, it constitutes a recent challenge. In this paper, we propose a novel recommender system for P2P social network. The principal objective is to help users to discover the most relevant content shared by their friends. Performance evaluations show that our proposed model is globally satisfactory compared to existing similar solutions.

Keywords

Decentralized Social Network, Peer To Peer, Recommender System, Collaborative Filtering, Cold start.

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