X-hinter: a framework for implementing social oriented recommender systems

Abstract

Accordingly to the nature of data-driven applications that produce information overload, users need a support to make choices, even without sufficient personal experience of the alternatives. In this context, social networking techniques could be useful applied for finding affinities between users and filter information in a personalized way. After proposing a generalized model for social recommender systems, called X-Hinter, we describe a Java API that provides a set of libraries and tools to build social filtering systems in a wide range of domains. A prototype implementation, named DeHinter, shows the feasibility of the proposed approach in a P2P file sharing application.