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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 11    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 11, November 2011
Identifying weak subjects using association rule mining
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Author(s)
Anuradha.Tadiparthi, Satya Prasad.R, Tirumala Rao S.N
KEYWORDS
Association Rule mining, Apriori algorithm, Confidence, Data mining, Strong association rules, Support, Weak subjects
ABSTRACT
Many educational institutions in India today are concentrating on identifying the weak students and the subjects in which those students are weak in the current semester for improving their student results. They are even appointing a faculty member as a counselor to identify the weak students and to know in which courses the student is weak. After identifying this, this information will be given to the faculty who is teaching those courses so that he/she can take a special interest on those students or even conduct special classes to those students. In this paper we propose that the data mining technique called association rule mining can be applied to identify the subjects in which the students are weak in the current semester using previous semester's results.
References
[1] Agrawal, R., Imielinski, T., and Swami, A. N. 1993. Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIG-MOD International Conference on Management of Data, 207-216.

[2] Han, J. and Kamber, M. 2000. Data Mining Concepts and Techniques. Mor-gan Kanufmann page no:230-240

[3]. R. Agrawal and R. Srikant, “FastAlgorithms for Mining Association Rules,” Proc. 20th Int’l Conf. Very Large Data Bases (VLDB ’94), pp. 487-499, 1994

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