| With the deepening of the application of database, the size of database expands quickly, people need to analyze these data and find the worthy information. Consequently data mining has become a research area with increasing importance. It includes lots of measures such as association rules mining, classification and prediction, clustering analysis and evolvement analysis. The main technique among the data mining measures is the association rules mining, which is also the most widely used data mining measure.In this paper, association rule mining was studied, researched and analyzed deep.And the author analyze and discuss the support-confidence framework, the correlativity and the validity. With introducing T-Testing, the Effect as a new evaluation criterion for association rules is proposed.The author analyze the current situation of Multi-media Teaching Evaluation and the related theory. Basic principles and data analysis purposes of Multi-media Teaching Evaluation is proposed in this paper. Following the author provide applications of the association rules in the analysis of Multi-media Teaching evaluation data in this research. In this paper,the association rules algorithm is introduced in the analysis of Multi-media Teaching evaluation data. A multi-layer data mining system based on the popular J2EE framework is presented. The system is modeled and developed separately using Webwork + Spring + Hibernate frame, which improve the maintainability, the reusability and the extendibility. The system is introduced in the analysis of multi-media teaching evaluation data. The result shows that introducing effect based on common approach to association rules mining for the analysis of Multi-media Teaching evaluation data is feasible and valuable and can not only effectively overcome the shortage of the existing evaluation criterion for association rules but also reduce the creation of redundant rules. |
