Mineração de Regras de Associação para Seleção de Oferta de Cursos de Especialização

Marcos André S. KutovaClodoveu A. Davis Jr.

This paper presents association rule mining on data from a poll on the interest of undergraduate students on a range of graduate courses offered by a university. The goal was to uncover unexpected relationships among courses, to support the decision making process as to the potential competition among them. Generation of association rules allowed the authors to point out situations in which two or more courses share roughly the same group of interested students, and may therefore divide their potential public, possibly making each other economically unfeasible. Conclusions include recommen- dations on strategies for the seasonal offering of graduate courses.

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