Resource Recommendation Using Adaptive Automaton

Recommender systems identify preferences of a certain user, as well as the rest of a community, related to the available resources, aiming at providing personalized resources to the users. This paper presents a recommender system using an adaptive automaton to analyze the existing relationships among resources and users, and determine the possible personalized recommendations. An experiment is presented in order to verify and analyze the generated recommendation on the developed system.