Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Javubar Sathick, K.
- Extraction of Actionable Knowledge to Predict Students' Academic Performance Using Data Mining Technique-an Experimental Study
Abstract Views :538 |
PDF Views:4
Authors
Affiliations
1 Department of Computer Applications, BSA University, Chennai, Tamil Nadu., IN
2 B.S. Abdur Rahman University, Chennai, Tamil Nadu., IN
1 Department of Computer Applications, BSA University, Chennai, Tamil Nadu., IN
2 B.S. Abdur Rahman University, Chennai, Tamil Nadu., IN
Source
International Journal of Knowledge Based Computer System, Vol 1, No 1 (2013), Pagination: 28-32Abstract
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
References
- Pandey, U. K. & Pal, S. (2011). Data Mining: A prediction of performer or underperformer using classification. International Journal of Computer Science and Information Technologies, 2(2), 686-690.
- Lakshmi, T. M., Martin, A., Begum, R. M. & Venkatesan, V. P. (2013). An analysis on performance of decision tree algorithms using student’s Qualitative data. International Journal of Modern Education and Computer Science, June, 5(5), 18-27.
- Singh, C., Gopal, A. & Mishra, S. (2011). Management faculty performance evaluation with signed and unsigned student feedback using linear regression technique. International Journal of Information Technology and Knowledge Management, 4(2), 591-594.
- Thai-Nghe, N. Busche, A. & Schmidt-Thieme, L. (2009). Improving Academic Performance Prediction by Dealing with Class Imbalance. International Swaps and Derivatives Association, (pp. 878-883).
- Kumutha, S. & Sathick, K. J. (2013). Performance Prediction and Analysis of a University using Data Mining Technique. National Conference on Advanced Computing Technology.
- Thai-Nghe, N., Drumond, L. & Horv'ath, T. (2011). Matrix and Tensor Factorization for Predicting Student Performance. 3rd International Conference on Computer Supported Education.
- Sinhgad, C. S., Gopal, A. & Mishra, S. (2012). Faculty performance prediction from student feedback using linear regression technique. International Journal on Computational Sciences and Applications, 2(4), 1-4.
- Shreenath, A. & Madhu, N. (2012). Discovery of students’ academic patterns using data mining techniques. International Journal on Computer Science and Engineering, 4(6), 1054-1062.
- Mashat, A. F. S. & Khedra, A. M. (2012). Decision Support System Based Markov Model for Performance Evaluation of Students Flow in FCITKAU. International Conference on Communication and Information Technology.
- Bhardwaj, B. K. & Pal, S. (2011). Data Mining: A prediction for performance improvement using classification, International Journal of Computer Science and Information Security, 9(4), 136-140.
- Basha, S. K. A. H. & Kumar, Y. R. R. (2012). Predicting student academic performance using temporal association mining. International Journal of Information Science and Education, 2(1), 21-41.
- Kabakchieva, D. (2013). Predicting student performance by using data mining methods for classification. Cybernetics and Information Technologies, 13(1), 61-72.
- Osmanbegović, E. & Suljić, M. (2012). Data mining approach for predicting student performance. Economic Review - Journal of Economics and Business, 10(1), 3-12.
- Tair, M. M. T. & El-Halees, A. M. (2012). Mining educational data to Improve student’s performance: A case study. International Journal of Information and Communication Technology Research, 2(2).