Ontological Framework for analyzing Student’s Emotional behavior performance enhancement using Fuzzy Logic
DOI:
https://doi.org/10.61841/8krvmd05Keywords:
Personality traits,, Semantic feedback, Ontology, Fuzzy Logic.Abstract
Personality refers to variations in one’s personal attributes subjected to various events throughout the accustomed life cycle in an individual. The projection of the individual’s mind in a behavioral activity also depicts one’s personality. In the paper a framework for analyzing a University Student’s performance efficiency for a job at workplace has been proposed. Students have been classified psychologically for determining overall efficiency based on different aspects such as emotional level, holistic approach, confidence level, stress and time management. The psychological factors and the relationships between them is depicted as an Emotion Ontology which gives a clear understanding for the system to be developed in the future based on the framework. By improving the individual traits efficiency of a person can have ameliorations which get reflected in the person’s work environment. The data set for training the proposed system is to be collected through questionnaires from which linguistic values are fed as input to the fuzzy Inference Engine along with association rules. The output of the system would also be a linguistic value with which the efficiency of the person is determined.
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1. Kulhavy, R. W., Wager, W. Feedback in programmed instruction: Historical context and Implications for practice in Interactive instruction and feedback. pp. 3-20(1993).
2. edro J. Muñoz-Merino1, Abelardo Pardo, Maren Scheffel, Katja Niemann, Martin Wolpers, Derick Leony, and Carlos Delgado Kloos, ”An Ontological
3. Framework for Adaptive Feedback to Support Students while Programming”, International Semantic Web Conference.(2011).
4. Devadoss, Nilavu, and Sivakumar Ramakrishnan. "Development of Fuzzy Rough Features in Ontology Knowledge Representation.” Journal of Engineering Technology, Volume 3, July. 2015, Pages 114-134.
5. Shruti.S Jamsandekar, R.R Mudholkar, “Performance Evaluation by Fuzzy Inference Technique”, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-3, Issue-2, May 2013.
6. F. Bobillo and U.Straccia, "Fuzzy ontology representation using OWL 2", Int. J.Approx. Reason., vol. 52, no. 7, pp. 1073-1094, Oct. 2011.
7. Tho, Quan Thanh, et al."Automatic fuzzy ontology generation for semantic web." IEEE transactions on knowledge and data engineering 18.6 (2006): 842-856.
8. Banswal, Ritu, and Vishu Madaan. "SPACS: Students' Performance Analysis and Counseling System Using Fuzzy logic and Association Rule Mining." International Journal of Computer Applications 134.3 (2016): 12-17.
9. Shah, Ameet D., and S. A. Ladhake. "Multi User feedback System based on performance and Appraisal using Fuzzy logic decision support system." 2013 International journal for engineering applications and technology (IJFEAT)-issues, Volume 2 Issue 1 pp. 1-10.
10. In goley, Shilpa N., and J. W. Bakal. "Evaluating Students Performance using Fuzzy Logic." International Conference, IJCA Proceedings on International Conference on Recent Trends in Information Technology and Computer Science, ICRTITCS (9) (2012).
11. Patil, Suvarna, Ayesha Mulla, and R. R. Mudholkar. "Best Student Award–A fuzzy Evaluation Approach." International Journal of Computer Science and Communication 3.1: 9-12, (2012).
12. Kaur, Tanumeet, and Amardeep Kaur. "Extension of a crisp ontology of fuzzy ontology" International Journal of Computational Engineering Research (ijceronline.com) Vol 2: 201-207.
13. Nilavu Devadoss et al., (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (5), 4304-4308. (2015).
14. Angham G. Hadi , Khudheir Jawad , Dina S. Ahmed , Emad Yousif. "Synthesis and Biological Activities of Organotin (IV) Carboxylates: A Review." Systematic Reviews in Pharmacy 10.1 (2019), 26-31. Print. doi:10.5530/srp.2019.1.5
15. Pandey Vimal, R.L.Subjective experience aspect of consciousness part II: Integration of classical and quantum concepts for emergence hypothesis (2009) NeuroQuantology, 7 (3), pp. 411-434.
16. Mensky, M.B.Everett interpretation and quantum concept of consciousness (2013) NeuroQuantology, 11 (SUPPL. 1), pp. 85-96.
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