Marcelo Garcia Manzato

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Unlike the traditional recommender systems, that make recommendations only by using the relation between user and item, a context-aware recommender system makes recommendations by incorporating available contextual information into the recommendation process as explicit additional categories of data to improve the recommendation process. In this paper, we(More)
One of the major challenges on Recommender Systems is how to predict users' preferences regarding contextual constraints in a group. There are situations which a user could be recommended with an appropriate item for one of their groups, but the same item may not be suitable when interacting with another user and/or group. We note that recommender systems(More)
This paper proposes a study and comparison of the combination of multiple metadata types to improve the recommendation of movie items according to users' preferences. We used four algorithms available in the literature to analyze the descriptions, and compared each other using all the possible combinations of the metadata extracted from two datasets, namely(More)
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