Modelo de Recomendación Basado en Conocimiento Empleando Números SVN

Knowledge based recommender systems despite its usefulness and high impact have some shortcomings. Among its limitations are lack of more flexible models, the inclusion of indeterminacy of the factors involved for computing a global similarity. In this paper, a new knowledge based recommendation models based SVN number is presented. It includes data base construction, client profiling, products filtering and generation of recommendation. Its implementation makes possible to improve reliability and including indeterminacy in product and user profile. An illustrative example is shown to demonstrate the model applicability.