Integrating Quality Criteria in a Fuzzy Linguistic Recommender System for Digital Libraries
Álvaro Tejeda-Lorente, Juan Bernabé-Moreno, Carlos Porcel, Enrique Herrera‐Viedma · Procedia Computer Science · 2014
Recommender systems can be used in an academic environment to assist users in their decision making processes to find relevant information. In the literature we can find proposals based in user’ profile or in item’ profile, however they do not take into account the quality of items. In this work we propose the combination of item’ relevance for a user with its quality in order to generate more profitable and accurate recommendations. The system measures item quality and takes it into account as new factor in the recommendation process. We have developed the system adopting a fuzzy linguistic approach.