Research And Application Of Personalized Recommend System Based On Peer To Peer Network

In this paper, we focus on the application of personalized recommend system on the peer to peer network. Nowadays, the research and application about personalized recommend has attracted a lot of attention. There are many problems and challenges in the aspects such as trust, realtime, scalability, recommending for mobile users and so on. This leads to the use of recommend system only settling on a certain level, and its development has been restricted. The purpose of the study is that according to the research and developing direction, analyzing the difference between peer to peer and C/S, thus building personalized recommend system on peer to peer network platform. By those efforts, the performance of recommend system could be better and it would has a bright development prospect.Based on the research domestic and overseas of recommend system and p2p network, all kinds of technology and arithmetic, we firstly build a bottom-layer correspondence mechanism, providing a powerful bottom-layer support for dynamic extending service. Secondly, we put forward a system architecture and multilayer p2p network architecture, design the main function modules in detail, and make a simulation experiment. Thirdly, we give performance evaluation. Finally, the progress on research and experiment as well as the further research task is pointed out.We mainly discuss and make some contributions to the problems such as system structure of recommd system, multilayer network, search arithmetic,reputation management,similar model building,bottom-layer correspondence etc.