A Recommendation Strategy Based on User Behavior in Digital Ecosystems

In this paper, we present a new vision of multimedia recommender systems based on an a novel paradigm that combines both analysis of user behavior and semantic descriptors of multimedia objects. In particular, we model recommendation as a two step process: first we propose a model of user behavior, based on a semantic network that captures the necessary knowledge of the domain of interest; second we propose a recommendation strategy based on both this kind of a-priori knowledge and on the current usage patterns, considering the actual and complex structure of multimedia data. We have implemented a prototype that supports our proposed recommendation strategy; eventually a real use of our system based on a 3D interface is presented and discussed.