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Reseach Article

Application of Association Rule Mining to Help Determine the Process of Career Selection

by Harini Peri, Preetham Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 94 - Number 16
Year of Publication: 2014
Authors: Harini Peri, Preetham Kumar
10.5120/16442-6052

Harini Peri, Preetham Kumar . Application of Association Rule Mining to Help Determine the Process of Career Selection. International Journal of Computer Applications. 94, 16 ( May 2014), 15-19. DOI=10.5120/16442-6052

@article{ 10.5120/16442-6052,
author = { Harini Peri, Preetham Kumar },
title = { Application of Association Rule Mining to Help Determine the Process of Career Selection },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 94 },
number = { 16 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 15-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume94/number16/16442-6052/ },
doi = { 10.5120/16442-6052 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:18:15.367557+05:30
%A Harini Peri
%A Preetham Kumar
%T Application of Association Rule Mining to Help Determine the Process of Career Selection
%J International Journal of Computer Applications
%@ 0975-8887
%V 94
%N 16
%P 15-19
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The enormous data present at a university can be analyzed to generate useful information regarding the career paths chosen by students over the last few years. This information can not only be used by the students for analyzing the scope of their chosen career path but also by various authorities in analyzing the present career trends and understanding the scope of improvement among the less chosen ones. Dynamic Itemset Counting algorithm is an Association Rule Mining Technique used to identify patterns from an enormous amount of data, such as the data present at a university's repository. This model is an attempt towards uncovering hidden patterns. The generated results of the algorithm help in giving useful insights to decision makers in helping them make better and informed decisions.

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Index Terms

Computer Science
Information Sciences

Keywords

Preferred attribute support confidence minimum support dynamic itemset counting algorithm