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Reseach Article

A Model for Mining Course Information using Vague Association Rule

by Anjana Pandey, K. R. Pardasani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 20
Year of Publication: 2012
Authors: Anjana Pandey, K. R. Pardasani
10.5120/9395-7825

Anjana Pandey, K. R. Pardasani . A Model for Mining Course Information using Vague Association Rule. International Journal of Computer Applications. 58, 20 ( November 2012), 1-5. DOI=10.5120/9395-7825

@article{ 10.5120/9395-7825,
author = { Anjana Pandey, K. R. Pardasani },
title = { A Model for Mining Course Information using Vague Association Rule },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 20 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number20/9395-7825/ },
doi = { 10.5120/9395-7825 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:02:59.704933+05:30
%A Anjana Pandey
%A K. R. Pardasani
%T A Model for Mining Course Information using Vague Association Rule
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 20
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are different university offering different types of courses over several years, and the biggest issue with that is how to get information to make course more effective. Association rule mining can be used to evaluate the course effectiveness and helps to look for in regards to changes in performance of the course. For Example there is a course offering different topics. We can say that the topics having full attendance are totally effective and carry no hesitation information. While there are some topics which are almost fully attendant carry some hesitation information. This hesitation information is valuable and can be used to make the course more effective and interesting. We use vague association rule to render that hesitation information and develop an algorithm to mine the hesitation information. Our experiments on real datasets verify that our algorithm to mine the Vague Association Rule is efficient. Compared with the traditional Association Rule mined from transactional databases, the Vague Association Rule mined from the AH-pair databases are more specific and are able to capture richer information.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hesitation Information Vague Association Rule AH pair