An analysis of peer similarity for recommendations in P2P systems

作者：Mekouar Loubna^*; Iraqi Youssef; Boutaba Raouf

来源：Multimedia Tools and Applications, 2012, 60(2): 277-303.

DOI：10.1007/s11042-010-0612-1

• Recommender system
• Similarity metrics
• Personalized recommendations
• Content adaptation
• Multimedia files
• Peer-to-Peer systems

In this paper, we propose a novel recommender framework for partially decentralized file sharing Peer-to-Peer systems. The proposed recommender system is based on user-based collaborative filtering. We take advantage from the partial search process used in partially decentralized systems to explore the relationships between peers. The proposed recommender system does not require any additional effort from the users since implicit rating is used. The recommender system also does not suffer from the problems that traditional collaborative filtering schemes suffer from like the Cold start and the Data sparseness. To measure the similarity between peers, we propose Files%26apos; Popularity Based Recommendation (FP) and Asymmetric Peers%26apos; Similarity Based Recommendation with File Popularity (ASFP). We also investigate similarity metrics that were proposed in other fields and adapt them to file sharing P2P systems. We analyze the impact of each similarity metric on the accuracy of the recommendations. Both weighted and non weighted approaches were studied.

• 出版日期2012-9