Volume 8 Number 9 ( Sep. 2013)
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JSW 2013 Vol.8(9): 2352-2359 ISSN: 1796-217X
doi: 10.4304/jsw.8.9.2352-2359

Improved Data Mining Algorithms Based on an Early Warning System of College Students

Lijuan Zhou1, Yuyan Chen2, Shuang Li2

1Department of Information Engineering College, Capital Normal University, Beijing, China
2Capital Normal University, Information Engineering College, Beijing, 100048, China

Abstract—In order to solve the problem of early warning of college students’ achievement, this paper proposes two improved algorithms for data pre-processing and mining warning factor. At first we put forward an improved K-Means algorithm which is not only ensures the accuracy of the original algorithm, but also improves the stability of the algorithm. Then we put forward an improved algorithm New_Apriori algorithm and analyze experiment result. The result shows that the amount of data access has been reduced significantly and efficiency has been improved. In the end of this paper, we built the early warning model of students’ achievement based on neural network. The result of experiment shows that the new algorithms improve the efficiency and accuracy of the early warning.

Index Terms—Data Mining; Cluster Analysis; Association Rules; BP Neural Network.

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Cite: Lijuan Zhou, Yuyan Chen, Shuang Li, "Improved Data Mining Algorithms Based on an Early Warning System of College Students," Journal of Software vol. 8, no. 9, pp. 2352-2359, 2013.

General Information

  • ISSN: 1796-217X (Online)

  • Abbreviated Title: J. Softw.

  • Frequency:  Quarterly

  • APC: 500USD

  • DOI: 10.17706/JSW

  • Editor-in-Chief: Prof. Antanas Verikas

  • Executive Editor: Ms. Cecilia Xie

  • Abstracting/ Indexing: DBLP, EBSCO,
           CNKIGoogle Scholar, ProQuest,
           INSPEC(IET), ULRICH's Periodicals
           Directory, WorldCat, etc

  • E-mail: jsweditorialoffice@gmail.com

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