The Research on Courses Correlation Based on the Intelligent Education Frame

Abstract

Recent years, with the development of machine learning and data mining technology, educational data mining gets more and more attentions by education experts and scholars. It is called “intelligent education†by us that through using machine learning and data mining technology, education-related work is improved after using the information mined from educational field data. Association rule mining is one of the key data mining technologies and its typical algorithms are apriori, kd-tree algorithm and so on. This paper uses its related algorithm in order to mine the association among school courses. But existing association rule mining algorithms have some shortcomings, such as low time efficiency and many obscure rules. This paper uses related proposed algorithm named “subset aprioriâ€. Through the experiments on three student score datasets, it proved that subset apriori algorithm is more efficient and less reluctant rules.