Applying Data Mining Techniques with Data of Campus Card System

Abstract In recent years, campus card system (CCS) has been widely used in universities. At the same time, the scale of the data stored in the database of the CCS is also increasing rapidly. Therefore, it would be better to adopt data mining techniques to reveal the status, causes and trends of students’ consumption data. In this research, the K-Means clustering algorithm is applied to the students’ consumption behavior. The Apriori algorithm is used to study the students’ consumption behavior and performance. The results not only improve the efficiency of student work but also help to build smart campus for our university.