Abdul Fattah Mashat; Mohammed M. Fouad; Philip S. Yu; Tarek F. Gharib

Discovery of Association Rules from University Admission System Data

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Author(s)

Abdul Fattah Mashat ^1,* Mohammed M. Fouad ¹ Philip S. Yu ² Tarek F. Gharib ¹

1. Faculty of Computing and Information Technology. King Abdulaziz University, Jeddah, Saudi Arabia

2. College of Engineering, University of Illinois, IL, USA King Abdulaziz University, Jeddah, Saudi Arabia

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2013.04.01

Received: 14 Jan. 2013 / Revised: 10 Feb. 2013 / Accepted: 2 Mar. 2013 / Published: 8 Apr. 2013

Index Terms

Educational Data Mining, Association Rules Discovery, University Admission System.

Abstract

Association rules discovery is one of the vital data mining techniques. Currently there is an increasing interest in data mining and educational systems, making educational data mining (EDM) as a new growing research community. In this paper, we present a model for association rules discovery from King Abdulaziz University (KAU) admission system data. The main objective is to extract the rules and relations between admission system attributes for better analysis. The model utilizes an apriori algorithm for association rule mining. Detailed analysis and interpretation of the experimental results is presented with respect to admission office perspective.

Cite This Paper

Abdul Fattah Mashat, Mohammed M. Fouad, Philip S. Yu, Tarek F. Gharib, "Discovery of Association Rules from University Admission System Data", International Journal of Modern Education and Computer Science (IJMECS), vol.5, no.4, pp.1-7, 2013. DOI:10.5815/ijmecs.2013.04.01

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International Journal of Modern Education and Computer Science (IJMECS)