Research on Construction of Universities Sports Management Information System Based on Data Mining

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Abstract:

The progress of computer and network technology provides the technical support for the information construction work in universities, along with the attention of the physique for the students in our country. In this paper, data mining technology combined with the universities sports teaching practice can achieve a sports performance management system based on data mining, and improve the quality of physical education teaching. Through the current situation of universities sports management and data mining can build universities sports management information system, the related value analysis and methods is important to build universities sports management information system based on data mining. The system uses the thought of data mining, which can provide the decision-making basis for sports teaching; In addition, the system structure of three layers makes the system in good adaptability and function expansibility with reduction of the maintenance workload for later.

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2702-2705

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November 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Agnes Bogairdi-Meszoly, Tihamer Levendovszky, Hassan Charaf. Performance Factors in ASP. NET Web Applications with Limited Queue Model . INES International Conference on Intelligent Engineering Systems. 2008, 253-257.

DOI: 10.1109/ines.2006.1689379

Google Scholar

[2] Breiman L Friedman, H R A, Stone C J. Classification Regression Trees. Wadsworth International Group, 2010, 134-139.

Google Scholar

[3] Fawaz A. Masoud, Dana H. Halabi, Deema H. Halabi. asp. net frameworks and JSP frameworks in model view controller implementation . IEEE, 2009, 3593-3598.

DOI: 10.1109/ictta.2006.1684998

Google Scholar

[4] Mohammad Jafar Tarokh. Javad Soroor. Supply Chain Management Information Systems Critical Failure Factors . IEEE. 2010. 425-431.

DOI: 10.1109/soli.2006.236430

Google Scholar

[5] S Chaud huri, U Fayyad, J Bernhardt. Scalable Classification over SQL Databases. In Proc. ICDE-99, Sydney, Australia, IEEE Computer Society. 2009, 472-478.

Google Scholar

[6] Jian wei Han, Miehe line Kamber. Data Mining Concepts and ethnique. Morgan Kanfmarin Public thing, 2010, 80-88.

Google Scholar