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Issue:Generalized net model of using data mining techniques for process of undergraduate matriculation in a digital university

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Title of paper: Generalized net model of using data mining techniques for process of undergraduate matriculation in a digital university
Author(s):
Anthony Shannon
Warrane College, University of New South Wales, Kensington, 1465, Australia,
tony@warrane.unsw.edu.au
Evdokia Sotirova
“Prof. Asen Zlatarov” University, Bourgas 8010, Bulgaria
esotirova@btu.bg
Daniela Orozova
Burgas Free University
orozova@bfu.bg
Presented at: 11th IWGN, Sofia, 5 December 2010
Published in: Conference proceedings, pages 1—6
Download:  PDF (180  Kb, Info)
Abstract: Data mining techniques are used in the area of undergraduate matriculation process in a digital university to better manage applicants recruitment efforts. These techniques determine how likely a particular student matriculate based on their interests, geographic location, and scholastic ability. Predicting allows to focus resources of the university staff to those applicants most likely to attend. The present paper describes the model of the applying data mining tools for the undergraduate matriculation process in a digital university. For the purpose we use Generalized Nets. The opportunity of using GNs as a tool for modelling such process is analyzed as well.
Keywords: Generalized nets, Modelling, Data mining tools, Digital university, E-learning.
References:
  1. Atanassov, K. Intuitionistic Fuzzy Sets, Springer, Heidelberg, 1999
  2. Atanassov, K. On Generalized Nets Theory. Prof. M. Drinov Academic Publ. House, Sofia, 2007.
  3. Atanassov, K., Generalized Nets. World Scientific, 1991.
  4. Bishop C. M., Neural networks for pattern recognition, Oxford university press, ISBN 0 19 853864 2 , 2000
  5. Haykin, S. “Neural Networks: A Comprehensive Foundation”, Prentice Hall, N.J., 1999
  6. M.T.Hagan, H.B.Demuth, M.Beale, “Neural Network Design”, PWS Publishing Company, Boston, 1996
  7. Melo-Pinto, P., T. Kim, K. Atanassov, E. Sotirova, A. Shannon and M. Krawczak, Generalized net model of e-learning evaluation with intuitionistic fuzzy estimations, Issues in the Representation and Processing of Uncertain and Imprecise Information, Warszawa, 2005, 241-249.
  8. Shannon, A., D. Langova-Orozova, E. Sotirova, I. Petrounias, K. Atanassov, M. Krawczak, P. Melo-Pinto, T. Kim. Generalized Net Modelling of University Processes. KvB Visual Concepts Pty Ltd, Monograph No. 7, Sydney, 2005.
  9. Shannon, A., E. Sotirova, I. Petrounias, K. Atanassov, M. Krawczak, P. Melo-Pinto, T. Kim, Intuitionistic fuzzy estimations of lecturers’ evaluation of student work, First International Workshop on Intuitionistic Fuzzy Sets, Generalized Nets & Knowledge Engineering, University of Westminster, London, 6-7 September 2006, 44-47
  10. Shannon, A., E. Sotirova, I. Petrounias, K. Atanassov, M. Krawczak, P. Melo-Pinto, T. Kim, Generalized net model of lecturers’ evaluation of student work with intuitionistic fuzzy estimations, Second International Workshop on Intuitionistic Fuzzy Sets, Banska Bystrica, Slovakia, 3 December 2006, Notes on IFS, Vol. 12, 2006, No. 4, 22-28.
  11. Shannon, A., E. Sotirova, K. Atanassov, M. Krawczak, P. Melo-Pinto, T. Kim, Generalized Net Model for the Reliability and Standardization of Assessments of Student Problеm Solving with Intuitionistic Fuzzy Estimations, Developments in Fuzzy Sets, Generalized Nets and Related Topics. Applications. Vol. 2, System Research Institute, Polish Academy of Science, 2008, 249-256.
  12. Shannon, A., E. Sotirova, K. Atanassov, M. Krawczak, T. Kim, Generalized Net Model of a Student’s Course Evaluation with Intuitionistic Fuzzy Estimations, Advanced Studies Contemporary Mathematics, Vol. 18 (2), 2009 (in press).
  13. Shannon, A., K. Atanassov, E. Sotirova, D. Langova-Orozova, M. Krawczak, P. Melo-Pinto, I. Petrounias, T. Kim, Generalized Nets and Information Flow Within a University, Warszawa, 2007.
  14. Sotirov, S., D. Orozova, E. Sotirova, Neural network for defining intuitionistic fuzzy sets in e-learning, Тhirteen Int. Conf. on IFSs, Sofia, NIFS Vol. 15, 2009, 33-36.
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