Optimization of Teaching Management System Based on Association Rules Algorithm

Abstract

The teaching management department carries all the work related to teaching in the whole school. A scientific, efficient, and complete teaching management system cannot only help the teaching management department improve work efficiency and quality but also greatly reduce many problems caused by manual labour risk. This paper designs and implements a teaching management system based on an improved association rule algorithm. First, aiming at the low efficiency of the Apriori algorithm for mining association rules, an association rule model based on interest is proposed. Second, use the MapReduce calculation model to partition the transaction database, then use the improved Apriori optimization algorithm for mining, and finally merge the mining results to obtain frequent itemsets. Through experiments, the optimized algorithm has greatly improved selection mining and computing time than traditional algorithms.