Research Of Association Rules In The Ways Of University Classroom Teaching Quality Assessment System

With the rapid development of information technology, making datas in all kinds of fields have an incredible rocket,but the available effective information is limited.It is a common project we face that how to access the valuable and potential information from the vast amounts of datas.Data Mining provides people a new intelligent approach to understand data. Association rule is one of the most impotant technologies in data mining.In this paper,the analysis and mining research on datas are carried out that based on the research of association rules mining technology.Firstly, in the light of the shortcomings and lack,the match-degree is used instead of the confidence-degree,the rules generated by the match-degree method not only have higher relevance on before and after, but also reduce the generation of redundant rules.Secondly, on the basis of the research of Apriori algorithm,presents an improved boolean matrix-based Apriori algorithm to improve the performance of association rule algorithm.This algorithm uses the thoughts of Boolean matrix,just needs scan the database only once to get the frequent itemset,it improves the efficiency of algorithm.Finally, combined with the characters of the classroom teaching quality assessment datas,association rules algorithm will be applied to the determination of the classroom teaching quality assessment index system: Evaluation information as data sources.It is realized that the scientific determination of teaching quality assessment index system by use of the improved apriori algorithm.