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Extraction of Actionable Knowledge to Predict Students Academic Performance using Data Mining Technique - An Experimental Study

International Journal of Knowledge Based Computer Systems

Volume 1 Issue 1

Published: 2013
Author(s) Name: K. Javubar Sathick, A. Jaya | Author(s) Affiliation: B.S. Abdur Rahman University, Chennai, Tamil Nadu, India
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Abstract

Knowledge discovery in academic institution becomes more critical and crucial in terms of identifying the student’s performance. In the extraction of actionable knowledge from a large database the data mining plays a vital role. The actionable knowledge extraction provides a interestingness and meaning to the mined data. This paper focuses on the prediction of the student’s academic performance from the large student database. The mining algorithm like clustering and classification algorithm is revisited to predict the performance after initial mining of raw data. The main scope of this paper is to reveal the outcome of the performance analysis of a student .This work will help the university to reach betterment in providing the quality input to the student community and impart the knowledge effectively.

Keywords: Actionable Knowledge, Classification, Clustering, Prediction and Analysis

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