Educational Data Mining using Improved Apriori Algorithm
نویسندگان
چکیده
Educational Data Mining (EDM) is an emerging interdisciplinary research area that deals with the development of methods to explore data originating in an educational context. EDM uses different computational approaches to analyze educational data in order to study educational questions. Different data mining techniques has been applied in this area. One of the most widely used techniques in EDM is association rules mining. Apriori algorithm is the first and best-known algorithm for association rules mining. This paper surveys the most relevant studies carried out in EDM using Apriori algorithm. Based on the Apriori algorithm analysis and research, this paper points out the main problems on the application Apriori algorithm in EDM and presents an improved support-matrix based Apriori algorithm. The improved Apriori algorithm proposed in this research uses bottom up approach along with standard deviation functional model to mine frequent educational data pattern.
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