Information Reconstruction of Student Management Work Based on Association Rules Mining.

Abstract

In recent years, as the country has paid more and more attention to the education, informatization of student management has become more and more important. This article aims to study how to reconstruct the informatization of student management which is based on association rule mining. This article mainly introduces association rule mining and student management informationization. Based on data mining, an algorithm for association rules is proposed, and the algorithm is used to mine student management informationization. From the data in the experiment, it can be seen that the efficiency of traditional student management is between 25% and 35%, whereas the efficiency of student management information based on association rules is between 64% and 72%. It can be seen that the efficiency of student management work combined with association rule mining is significantly higher than that of traditional management methods. From the data, we can see that in 2017, the development trend of colleges and universities adopting information management rose from about 5.4% to about 11%, and the development trend of colleges and universities adopting information management rose from about 7.5% to about 33% in 2018. In student management, the simplification of information can effectively improve the efficiency of student management, so the reconstruction of student management information based on association rule mining has become very important.