A Peer-to-Peer Recommender System with Privacy Constraints

A recommender system can be used to suggest users potentially interesting content based on their previous consumption behavior Such services already became common in centralized systems, such as Amazon, and approaches exist for decentralized recommender systems. However common P2P recommender systems expose the user's preferences in the whole system. This is not desirable if privacy is required. Realization of a recommender system in a private P2P environment is not a trivial task, since we cannot gather the user data at central servers or just spread then in the community In this work we propose a private file sharing application based on social contacts. Instead of gathering all the information about users at one place the users exchange information only with their social contacts. We show how a personalized recommender system can be built in such an environment.