Big Data Oriented Mining and Implementation Analysis for Online Education Information

With the advent of the big data, the amount of data generated during the development of online education is also amazing. Therefore, online education based on big data guidance has become a hot research trend. Focusing on educational mining of big data and learning analysis techniques, this paper uses Apriori algorithm running on Hadoop to improve the efficiency of parallel computing, by studying the data set segmentation idea and optimization from the key value reduction. Then, we analyze and study the characteristics of educational big data, and perform data set processing for user-course access frequency data, which improves the accuracy of association rule mining and provides instructive information for school education decision-making and teaching management.