An Improved Apriori Algorithm Research Based On The Mobile Teaching Evaluation System

In the modern society of highly developed science and technology, we deal with a lot of data every day, and some we can easily obtain information, but some of the large-scale complex data, it is difficult to directly access to effective information of the data behind. Therefore, data mining technology in our life, help us to solve some complex problems.In college teaching evaluation system, there accumulated a large amount of data, most colleges and universities in education teaching only simple do data statistics and query these data, and a large amount of data in the implied more valuable knowledge or information is not used. The data mining technology can solve this problem.In this paper, the huge amounts of data using the mining association rules method carries on the analysis and research. Firstly introduces the related technology of data mining and the Apriori algorithm which is often used in the direction of the association rules, and explains the ideas of the algorithm in detail and the implementation process, according to some of the deficiencies in the Apriori algorithm, after optimizing algorithm based on the analysis of others thoughts, We presents an improved algorithm on the basis of a fewer scan the transaction database and reduce the candidate item sets the size. In the improved algorithm, it scan the database only once, and improves the speed of candidate itemsets generation, it can be more effective to produce the final frequent itemsets, reduces the time and space complexity of the algorithm.Finally, based on the data and information for our school student evaluation system, using the improved algorithm mines association rule,after that doing data collection and analysis from the result that some regularity and characteristics of our school’s teaching activities, teaching activities in the future are put forward based on the information of suggestions and improving measures.