Reginaldo Aparecido Gotardo

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Content recommendation in Web based educational systems aims to provide references to didactic and educational resources, attending the individual necessities of the students. This paper presents an approach for content recommendation based on three metrics, the interest a user has on resources, her or his preferences over the resources and the popularity(More)
In this paper we present an approach to treatment of the Cold-Start Problem in Recommendation System for Environment Education Web. Our approach is based on the concept of Coupled-Learning and Bootstrapping. Based on an initial set of data we apply algorithms traditional machine learning to cooperate with each other, forming various views on its outputs and(More)
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(More)
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