Discovery of Strongly Related Subjects in the Undergraduate Syllabi using Data Mining

@article{Tissera2006DiscoveryOS,
  title={Discovery of Strongly Related Subjects in the Undergraduate Syllabi using Data Mining},
  author={W. M. R Tissera and R. I. Athauda and H. C. Fernando},
  journal={2006 International Conference on Information and Automation},
  year={2006},
  pages={57-62}
}
Data mining consists of a variety of techniques that can be used to extract relevant and interesting knowledge from vast amounts of data. Data mining has been successfully applied in a variety of domains to gain knowledge significant in decision making. In this paper, we present a real-world experiment conducted in an ICT educational institute in Sri Lanka. Our experiment considers a data repository consisting students' performance in a large ICT educational institution. We apply a series of… CONTINUE READING
Highly Cited
This paper has 17 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
Showing 1-9 of 9 references

Statistics for managers and economists

  • G. Keller, B. Wrack
  • 2002
Highly Influential
7 Excerpts

Sri Lanka Report: Status of education

  • T. De Mel
  • MDG implementation.",
  • 2006
1 Excerpt

WebSite Mining: A new way to spot Competitors,Customers and suppliers in the World

  • M. Ester, H. Kriegal, M. Schubert
  • Wide Web.",
  • 2002

Cross -sell: A Fast Promotion - Turntable Customer item Recommendation Method

  • B. Kitts, D. Freed, J Kommers
  • Based on Conditionally Independent Probabilities…
  • 2000

Idan.Y., and Pinkas.G., "Discovery of Fraud Rules for Telecommunications - Challenges and Solutions

  • S. Roset, U. Murad, E. Neumann
  • 1999

Similar Papers

Loading similar papers…