Pages: 61-69
Codes: 378.146 74.480.28
Title: Improving quality of knowledge management system of higher education institution by use of data mining solutions
Authors: Nagornyy S.A.
Abstract: Article analyzes possibilities of usage data mining solutions in educational process management, describes main steps of creating students success rate model and evaluates results of modelingt.
Keywords: Data mining, knowledge management system, students success rate, higher education institution, educational data mining.
List of references:
1. Andonie R. Extreme data mining: Inference from small datasets // International Journal of Computers, Communications & Control. 2010. V(3).
2. Baker R.S.J.D., & Yacef K. The state of educational data mining in 2009: A review and future vision // Journal of Educational Data Mining. 2009. Vol. 1. Issue 1. PP. 3-17.
3. Becerra-Fernandez I., Gonzales A., & Sabherwal R. Knowledge management, challenges, solutions, and technologies. Prentice Hall: Pearson, 2004.
4. Bukowitz W.R., & Williams R.L. The knowledge management fieldbook. Prentice Hall, 2000.
5. Data Mining Concepts: SQL Server 2014. Microsoft Developer Network, 2014 // [ ]: http:// msdn.microsoft.com/ru-ru/library/ ms174949.aspx.
6. Marjeticˇ D., & Lesjak D. Financing of higher education and the role and dilemmas of tariff groups // International Journal of Management in Education. 2012. 6(1/ 2). . 56-72.
7. Natek S., & Lesjak D. Improving knowledge management by integrating HEI process and data models // The Journal of Computer Information Systems. 2013. 53(4). . 81-86.
8. Osei-Bryson K.-M. Towards supporting expert evaluation of clustering results using a data mining process model // Information Sciences. 2012. 180(3). . 414-431.
9. Tso G.K.F., & Yau K.K.W. Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks // Energy. 2007. 32. . 1761-1768.
10. Wan S., & Lei T.C. A knowledge-based decision support system to analyze the debris-flow problems at Chen-Yu-Lan River, Taiwan // Knowledge-Based System. 2009. 22(8). . 580-588.
11. Wang H., & Wang S. A knowledge management approach to data mining process for business intelligence // Industrial Management and Data Systems. 2008. 108(5).
12. Zhuang Z. Y., Churilov L., Burstein F., & Sikaris K. Combining data mining and case-based reasoning for intelligent decision support for pathology ordering by general practitioners // European Journal of Operational Research. 2009. 195. . 662-675.
13. Iyvazyan S.A., Buhshtaber V.M., Enukov I.S., Meshalkin L.D. Applied Statistics. Classification and reduction of dimension. Moscow: Finance and statistics, 1989. [In Russian].
14. Barseguan A.A., Kuprianov M.S., Stepanenko V.V., Holod I.I. Methods and models of data analysis. SPBPeterburg, 2004. [In Russian].
15. Milner B.Z. Knowledge management: organizational evolution and revolution. Moscow, 2003. 176 p. [In Russian].
16. Nonaka, Takeuchi. Organization producer of knowledge. Born and development in Japanese firms. Moscow. Olimp Business, 2003. 320 p. [In Russian]