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A Data Mining Model to Improve Placement

by Ravi Tiwari, Awadhesh Kumar Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 12
Year of Publication: 2015
Authors: Ravi Tiwari, Awadhesh Kumar Sharma
10.5120/21283-4274

Ravi Tiwari, Awadhesh Kumar Sharma . A Data Mining Model to Improve Placement. International Journal of Computer Applications. 120, 12 ( June 2015), 36-38. DOI=10.5120/21283-4274

@article{ 10.5120/21283-4274,
author = { Ravi Tiwari, Awadhesh Kumar Sharma },
title = { A Data Mining Model to Improve Placement },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 12 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 36-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number12/21283-4274/ },
doi = { 10.5120/21283-4274 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:06:04.726257+05:30
%A Ravi Tiwari
%A Awadhesh Kumar Sharma
%T A Data Mining Model to Improve Placement
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 12
%P 36-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Education data mining is one of the growing fields of the present time. as it grows many issues to improve system comes in the notice one of them is improvement of the placement. Placement is a very important issue for any educational organization. Every organization wants to improve its placement. Success of any educational institute is measured by the placed student of the organization. This paper actually deals with the application of neural network to the educational data to improve placement. It takes education data i. e student data as a input and predict the status of placement for the student. it also suggest the best field according to nature of the student data for particular student which have a chance to place. So through this educational organization can predict the placement of each student and can work according to it to improve the placement of the organization.

References
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  2. Nguyen N. , Paul J. , and Peter H. , a comparative analysis of techniques of predicting student performance. In the proceeding of 37th ASEE/IEEE frontiers in education.
  3. I. H. , M. Paris , L. S. Affecndy , improving prediction performance using voting technique in data mining , in world academy of science, vol 38 , 2010
  4. Al- Radaideh , Al-Shwakfa , mining student data using decision tree ,in international Arab conference on information technology , 2006
  5. Cesar V. , Javier B. , liela S. ,recommendation in higher education using data mining , educational data minng conference 2009
  6. Tripti mishra , Dr. dharminder kumar , dr. sangeeta gupta , mining student data for performance prediction , fourth international conference on advance computing and communication technologies, 2014
Index Terms

Computer Science
Information Sciences

Keywords

Educational data mining predication random tree

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