Discovery of Association Rules from University Admission System Data
Автор: Abdul Fattah Mashat, Mohammed M.Fouad, Philip S. Yu, Tarek F. Gharib
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 4 vol.5, 2013 года.
Бесплатный доступ
Association rules discovery is one of the vital data mining techniques. Currently there is an increasing interest in data mining and educational systems, making educational data mining (EDM) as a new growing research community. In this paper, we present a model for association rules discovery from King Abdulaziz University (KAU) admission system data. The main objective is to extract the rules and relations between admission system attributes for better analysis. The model utilizes an apriori algorithm for association rule mining. Detailed analysis and interpretation of the experimental results is presented with respect to admission office perspective.
Educational Data Mining, Association Rules Discovery, University Admission System
Короткий адрес: https://sciup.org/15014535
IDR: 15014535
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