Association Rule Mining Algorithm And It's On Vocational School Teaching Evaluation System Applied Research

Data mining is applying a series of techniques to collect information and knowledge from large databases or data warehouses that are interested by people. The purpose of the association analysis is mining the relationships that are hidden in the data, and the correlations between the items are described by using the association rules. It reflects the close degree or relationship between data items in a group. As an important branch of data mining, association rules have been used in many fields, but have not yet been widely used in the field of education.Teaching evaluation is based on the related policies, regulations, personnel training target, the use of education evaluation theory and methods, the teaching process and carry out activities to make value judgments in comprehensive, objective, and impartial ways on the teachers'job performances. In order to improve the deficiency in the teaching process, the teaching evaluation should be based on the teaching effect, to determine the scientific evaluation system, to find out the various influential factors of the teaching quality and effect. Teaching evaluation process is complex, multi-factor and fuzziness etc,the evaluation results may be deviated from the actual situation been evaluated. Therefore, the enhancement of scientific, objectivity and accuracy of the teaching evaluation is a very important topic in the modern teaching evaluation.The discovery of the association rules can be decomposed into two steps. The first step consists of finding all the frequent item-sets and the second step involves using the frequent item-sets to generate strong association rules. The Apriori algorithm is a classical algorithm that generates frequent item-sets. The basic idea of it is to use the layer-by-layer search iterative method for generating the frequent item-sets. Due to the multiple scanned databases and the large number of the candidate item-sets generation, it is time consuming to perform such algorithm and results in low efficiency for the mining process.This paper analyzes the classical Apriori algorithm and provides an improved Apriori algorithm to counter its'deficiency. This paper draws lessons from both domestic and foreign college teaching evaluation experiences and combines the reality of vocational schools to propose a set of teaching evaluation system. On this basis the teaching evaluation data mining module is designed and how the large amount of data in the evaluation system and the association rule mining are used for data mining research. Finally, the paper discussed how the improved algorithm is applied to the evaluation of teaching quality and the students'achievement data mining to obtain the linkage between the impact of teaching and the titles and ages of the teachers and the connection between one course grade and other courses'grades.