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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

The Design of College Student Growth Management System Based on Data Mining

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DOI: 10.25236/iceeecs.2018.057


Jiaqi Yuan, Shi Cheng, Jian Lu

Corresponding Author

Jiaqi Yuan


The concept of “big data” has been mentioned much more times than ever before. At present, the hardware and distributed system with high performance can help us process the data more quickly, and handle “all data” instead of “random data”. It is not necessary to depend on the sampling method when dealing with all the data and the result will be more reasonable. College student growth management system is designed to solve the problems such as “what kind of job will suit me” or “what courses will bring troubles for me”. Employment guidance works by finding similar students in database by using collaborative filtering algorithm. Academic warning tries to find rules in the courses that students often fail with the classic Apriori algorithm.


Management system based on data mining, college student growth, design.