Document Type : Original Research Paper

Authors

1 ICT Research Institute, Jahad Daneshgahi, Tehran, Iran

2 ICT Research Institute, Jihad Daneshgahi, Tehran, Iran

Abstract

In this study, firstly two challenges ahead of SMEs in doing need assessment & educational planning are considered. Then the issue of finding and selecting training courses is elaborated. Afterwards, a system of recommending training courses using case-based reasoning and Fuzzy Model is presented in order to identify the need assessment of firms as well as planning a suitable curriculum. The case-based reasoning is based on this principle that similar problems have similar solutions. In the knowledge base (case base) of this methodology in which the information & records of the past are gathered as cases, helps to collect & maintain the experts' knowledge in the proposed system. In this system, the Fuzzy model has been used to cope with the ambiguities & uncertainties in case representation and retrieval phase. EFQM (European Foundation for Quality Management) is applied for case modeling. Besides, in order to overcome the cold start problem, a module that is called SMART (Supplementary Module to Accomplish Recommending Task) has been used in which infer as an expert. Finally, this system is evaluated and the results are reported.

Keywords

Main Subjects

[1] Hamburg I. and Engert S., Competency-based Training in SMEs: The Role of ELearning and E-Competence, In Proceedings of the 6th IASTED International Conference Web-based Education, Chamonix, France March, 2007, pp.189-193. [2] Roy A. and Raymond L., Meeting the Training Needs of SMEs: is e-Learning a Solution? The Electronic Journal of e- Learning, Vol.6, No.2, July 2008, pp. 89 – 98. [3] Zadeh L.A., Fuzzy sets Information and Control, 1965, pp. 338-353. [4] Zimmerman H.J., Fuzzy Sets Theory and Its Applications, 3rd ed., Kluwer- Nijhoff, Amsterdam, 1996. [5] Aamodt A. and Plaza E., Case-Based Reasoning: Foundational issues, AI Communications, Vol.7, No.1, 1994, pp. 39-59. [6] Mullins R. and et al., A Web Based Intelligent Training System for SMEs, The Electronic Journal of e-Learning, Vol.5, No.1, 2007, pp. 39-48. ]7 ]مرادی منمش زهرا ، درزی محمد و اصغری وبیب اددد، بررسی و تحلیل فاکتورهمای اساسی در طراوی ی سیستم توصیهگر، دومیآ کنررانس شهر الکترونیکی، خرداد، 0399د [8] Chang P., Liu C. and Lai R., A fuzzy case-based reasoning model for sales forecasting in print circuit board industries, Expert Systems with Applications, 2008, pp. 2049–2058. [9] Chaudhury S.S., Singh T. and Goswami S.P., Distributed fuzzy case based reasoning, Applied Soft Computing, Vol. 4, 2004, pp. 323–343. [10] Bonissone P. and Cheetham W., Fuzzy CaseBased Reasoning for Residential Property Valuation, Handbook on Fuzzy Computing, Oxford University Press, 1998. طراوی ی سامانه توصیهگر ترکیبی ددد نشریه علمی پژوهشی فناوری آموزش، سال پنجم، جلد 5 ،شماره 2 ،زمستان 9831 918 [11] Dubois D., Esteva F., Garcia P., Godo L., López de Màntaras R. and Prade H., Fuzzy set-based models in case-based reasoning, IIIA Research Report, 1997, pp.97-109. [12] Ma Z., Hu J., Zhao S., and Huang J., Mobile Network Optimization Using Fuzzy Case-Based Reasoning for GSM, In Proceedings of the 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, IEEE Computer Society, Washington D.C, July, 2009, pp.461- 464. [13] Jaczynski M. and Trousse B., Fuzzy logic for the retrieval step of a case-based reasoned, in proceeding of the EWCBR'94, 1994, pp.313- 321. [14] Hansen B.K., Weather Prediction Using CaseBased Reasoning and Fuzzy Set Theory, Master of Computer Science thesis, Technical University of Nova Scotia. Canada, 2001. [15] Darzi M., Manesh Z.M., Hosseini M., Liaei A.A. and Asghari H., FCRS: A Fuzzy Casebased Recommender System for SMEs, In the proceeding of International Conference on Education and Information Technology, Chongqing, China, September, 2010 , pp.17-21. [16] Burke J. and Sandvig R., AACORN: A CBR recommender for academic advising, DePaul University, 2000. [17] Bendakir N. and Aimeur E., Using association rules for course recommendation, In Proceedings of the AAAI Workshop on Educational Data Mining, July, 2006 , pp.31–40. [18] Farzan R. and Brusilovsky P., Social navigation support in a course recommender system, In Proceedings of the 4th International Conference on Adaptive Hypermedia and Adaptive Webbased Systems, June, 2006, pp.91–100. [19] Ching Hsu I., SXRS: An XLink-based Recommender System using Semantic Web technologies, Expert Systems with Applications, Vol.36 No.2, March, 2009, pp. 3795-3804. [20] Saidi-Mehrabadi M., RezaeiSadrabadi M. and Mohammadian I., A new method to fuzzy modeling and its application in performance evaluation of tenants in incubators, In The International Journal of Advanced Manufacturing Technology, April, 2008, pp.192-201. [21] Benítez J.M., Martín J.C. and Román C., Using fuzzy number for measuring quality of service in the hotel industry, Tourism Management, Vol.28,No.2, April, 2007, pp.544–555. [22] Avramenko Y. and Kraslawski A., Case based design: Application in process Engineering, Springer-Verlag, Berlin, Heidelberg, 2008. [23] Kolodner J., Cased-based reasoning. Morgan Kaufmann, San Mateo, CA, 1993. [24] Chen S.J., A new similarity measure of generalized fuzzy numbers based on geometric-mean averaging operator, IEEE International Conference on Fuzzy Systems, BC, Canada Vancouver, 2006, pp.1879-1886. [25] Wilke W. and Bergmann R., Techniques and knowledge used for adaptation during casebased problem solving, In Tasks and Methods in Applied Artificial Intelligence, Springer Berlin / Heidelberg, 1998, pp.497-506. [26] Wilke W. and Bergmann R., Techniques and knowledge used for adaptation during casebased problem solving, In :Tasks and Methods in Applied Artificial Intelligence, Springer Berlin / Heidelberg, 1998, pp.497-506. [27] Burke R.D., Hybrid recommender systems: Survey and experiments, User Model, UserAdapt. Interact, Vol.12, No.4, 2002, pp.331– 370. [28] Breese J.S., Heckerman D. and Kadie C., Empirical analysis of predictive algorithms for collaborative filtering, in: Proc, of the 14th Annual Conf. on Uncertainty in AI, 1998, pp.43-52. [29] Chen S.J., Chen S.M. and Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. Applied Intelligence, Vol.26, No.1, 2007, pp.1-11. [30] Hanley J.A. and McNeil B.J., The Meaning and Use of the Area under a Receiver Operating Characteristic (RO
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