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Reseach Article

Use of Clustering to Improve the Standard of Education System

by Shishu Pal Singh, B. K. Sharma, N. K. Sharma
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 5
Year of Publication: 2012
Authors: Shishu Pal Singh, B. K. Sharma, N. K. Sharma
10.5120/ijais12-450175

Shishu Pal Singh, B. K. Sharma, N. K. Sharma . Use of Clustering to Improve the Standard of Education System. International Journal of Applied Information Systems. 1, 5 ( February 2012), 16-20. DOI=10.5120/ijais12-450175

@article{ 10.5120/ijais12-450175,
author = { Shishu Pal Singh, B. K. Sharma, N. K. Sharma },
title = { Use of Clustering to Improve the Standard of Education System },
journal = { International Journal of Applied Information Systems },
issue_date = { February 2012 },
volume = { 1 },
number = { 5 },
month = { February },
year = { 2012 },
issn = { 2249-0868 },
pages = { 16-20 },
numpages = {9},
url = { https://www.ijais.org/archives/volume1/number5/89-0175/ },
doi = { 10.5120/ijais12-450175 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:41:28.455571+05:30
%A Shishu Pal Singh
%A B. K. Sharma
%A N. K. Sharma
%T Use of Clustering to Improve the Standard of Education System
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 1
%N 5
%P 16-20
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with the application of Data Mining in the education sector. Generally the benefits of Data Mining are taken in the commercial fields. The study given, proposed a quiet different field where we can use the Data Mining and enhance the quality of education. In the given paper the performance of an institute students were studied. The study takes the performance of students in their examinations and their presence in the classrooms into consideration and finds a relation in them. The observed relation helps in identifying the group of students where the extra are required. The study was carried out using K – Means method of cluster analysis – a technique of Data Mining for finding the relevant records.

References
  1. SP Singh et. al / VSRD International Journal of CS & IT Vol. 1 (7), 2011, 501 – 510.
  2. C.-H. Cheng, Y.-S. Chen / Expert Systems with Applications 36 (2009) 4176–4184.
  3. ERDOGAN, TIMOR, “A data mining application in students database”, Journal of Aeronautics and Space technologies, July 2005 Vol. 2 No. 2 (53-57).
  4. Han, J., Kamber, W., “Data Mining Concepts and Techniques”, Morgan Kaufmann Publishers, USA, 5-10, 2001.
  5. Shi Na, Liu Xumin, Guan yong, “Research on k-means Clustering Algorithm” Proc. of the Third International Symposium on Intelligent Information Technology and Security Informatics, pp-63-67.
  6. Jiawei Han and Micheline Kamber, “Data Mining Concepts and Techniques”- A reference book.
  7. G.K. Gupta, “Introduction to Data Mining with Case Studies”, A reference book, Third edition, PHI publications.
  8. Singh Vijendra, Kelkar Ashwini, Sahoo Laxman, “An Effective Clustering Algorithm for Data Mining” Proc. of the 2010 International Conference on Data Storage and Data Engineering, pp-250-253.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining K – Means Cluster Distance Education