Discovery of Association Rules from University Admission System Data

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 K...

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Bibliographic Details
Published in:International journal of modern education and computer science 2013-05, Vol.5 (4), p.1-7
Main Authors: Fattah Mashat, Abdul, M.Fouad, Mohammed, S. Yu, Philip, F. Gharib, Tarek
Format: Article
Language:English
Subjects:
Algorithms
Computer science
Core curriculum
Curriculum Design
Data mining
Decision Support Systems
Education
Educational Environment
Information technology
Linear algebra
Relational data bases
Students
Teaching Methods
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Summary: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.
ISSN:2075-0161
2075-017X
DOI:10.5815/ijmecs.2013.04.01