Using Structural Knowledge In A Content-Based Recommender System

A Content-Based Recommender System lets to suggest now products to the user taking into account the likeness with the content (description) of other products that the user rated before. In this paper we present a recommender system that is capable of incorporating knowledge about the structure of the content of the products and help it to improve the recommendations. We use Bayesian Networks for modeling the structure of the products and the relations between them and the system users.