The goal of personalization in information retrieval is to tailor the search engine results to the
specific goals, preferences and general interests of the users. We propose a novel model
that considers the user's interests as sources of evidence in order to tune the accuracy of
documents returned in response to the user query. The model's fundation comes from
influence diagrams which are extension of Bayesian graphs, dedicated to decision-making
problems. Hence, query evaluation is carried out as an inference process that aims to …