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