With relative theory about technology of data mining and recommender model of user’s interest, this paper presents the method of MWFP-TREE based on the combination between recommender model idea of user’s weight and the minimum weighted FP-TREE method. Compared to traditional method, this method does not only carry out dimension reduction of raw data to improve the efficiency of a constructing tree but it also performs association rule mining and improves mining effect. This method is applied to mathematics teaching evaluation in one university and it finds out different evaluations from different students respectively considering students’ information and teachers’ information while it is not similar to traditional thought which is only to perform mining direction based on teachers’ information. Towards mining regulations and results, it provides significant referential values for objectivity of teaching evaluation and teaching directions.