The Application Of Data Mining To The College Enrollment And Educational Administration

With the fast development of Chinese Higher Education, and the rapid increasement of the students, the database of students is becoming larger. So it is significant to extract important information hidden in the database of students. The current database is only available for transaction management and information retrieval, but it can not find the hidden relation and rules. Aiming at this problem, this paper designed a novel database syetem with some alogrithms of data mining, and it can mine the important information hidden in the database. According to it, teaching work and college enrollment can be arranged effectively.The main work is as follows. The idea of applying data mining technology on educational administration and college enrollment work is introduced in this paper and the feasibility and necessity are analyzed. FP-growth algorithm and C4.5 algorithm are applied in this system to mine the knowledge hidden in the education administration and college enrollment database. Firstly, the interesting association rules are analyzed and mined from the school score and entrance score database with FP-growth algorithm. Then a system model constructed by C4.5 algorithm can predicted the graduation scores by entrance score. So the feasiable cultivation method and goal can be set down effectively, and the teaching work can also be guided. The system is designed with VC++6.0 and SQL Sever2000. The system includes server models, such as system management, student information, data preprocess, university information mining and report printing. According to the system, the data can be prepared and preprocessed, the knowledge hidden in the database can be mined, and the models can also be evaluated and analyzed.