Abstract—The rapid deployment of peer-to-peer (P2P) applications and the various shared contents have raised the problem of information overload. As a result, the users participating in a P2P network can no longer easily find the contents they really need. Recommendation systems are thus developed to suggest to the users the contents that are useful or valuable to them. But, the most of the current recommendation systems can not be easily applied to the P2P environment. In this paper, we will propose PORS (Peer-to-peer mOvie Recommendation System), which is a collaborative movie recommendation system in the P2P environment. To obtain the best recommendation results, PORS uses the download history and the ratings of watched movies of a user to make recommendation decisions. We are currently implementing the system and will have some system evaluations. We hope that PORS does provide satisfactory movie recommendations.
Index Terms—Peer-to-peer, recommendation system, collaborative filtering, push, agent
The authors are with Department of Information Management, National Changhua University of Education, Changhua, Taiwan (Tel: +886-4- 7232105 ext 7330; fax: +886-4-7211295. e-mail: firstname.lastname@example.org)
Cite: Chian Wang and Dai-Yang Lin, "PORS: A Peer-to-Peer Movie Recommendation System," International Journal of Future Computer and Communication vol. 1, no. 2, pp. 135-137, 2012.