Reudismam Rolim de Sousa

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Digital TV content providers are becoming widespread, with hundreds of programs available each day. The information overload makes difficult for the user to find programs of interest. To help the user, <i>Recommendation Systems (RS)</i> are a popular path. However, applying RS to some environments is not easy, either due to the lack or insufficiency of data(More)
—Integrated Development Environments (IDEs), such as Visual Studio, automate common transformations, such as Rename and Extract Method refactorings. However, extending these catalogs of transformations is complex and time-consuming. A similar phenomenon appears in intelligent tutoring systems where instructors have to write cumbersome code transformations(More)
—Recommendation systems are software tools and techniques that provide customized content to users. The col-laborative filtering is one of the most prominent approaches in the recommendation area. Among the collaborative algorithms, one of the most popular is the k-Nearest Neighbors (kNN) which is an instance-based learning method. The kNN generates(More)
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