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To enhance education, it is important to keep track of the students' progress and to use appropriate teaching strategies based on the current state of the students' knowledge. From this viewpoint, the problem of selecting an optimal control of the state of student's knowledge becomes a particular case of the general problem of controlling systems. Control theory has shown that in many situations,...
Recommender systems help users to find information that best fits their preferences and needs in an overloaded search space. Most of recommender systems research focuses on improving recommendation methods to obtain a higher accuracy in recommendations. However, the study of user's inconsistencies, so-called natural noise, is becoming a hot topic in Recommender Systems. In this contribution is proposed...
In the recent years, computational architectures have been proposed to allow teams assessment in collaborative training based on virtual reality. In the virtual environments, procedures are performed by a team of professionals acting simultaneously, as in real surgical rooms. It is important to verify if the group performed the procedure correctly or not. The assessment systems utilizes user and users...
Recommender systems are important for e-commerce companies as well as researchers. Recently, granular association rules have been proposed for cold-start recommendation. However, existing approaches reserve only globally strong rules; therefore some users may receive no recommendation at all. In this paper, we propose to mine the top-k granular association rules for each user. First we define three...
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