International Journal of Information Technology and Computer Science(IJITCS)
ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)
Published By: MECS Press
IJITCS Vol.9, No.8, Aug. 2017
Career Guidance through Multilevel Expert System Using Data Mining Technique
Full Text (PDF, 505KB), PP.22-29
In this paper, the author provides a framework for Multilevel Expert System to advice scholars for their future career. The proposed framework aims at providing information to decide the career paths for the academics. The emerging fields of Expert System, Education, and Data Mining are speedily providing new possibilities for collecting, analyzing and guiding the scholars in their careers. Many scholars suffer from taking a right career decision, only a few scholars took the right decision about their careers. A poor career decision of scholars may push his whole life in the dark. Nowadays selecting a right career becomes very difficult for the scholars. Among the works reported in this field, we concentrate only Experts Systems that deal with scholar's career selection problem through Data Mining technique.
Cite This Paper
Gufran Ahmad Ansari,"Career Guidance through Multilevel Expert System Using Data Mining Technique", International Journal of Information Technology and Computer Science(IJITCS), Vol.9, No.8, pp.22-29, 2017. DOI: 10.5815/ijitcs.2017.08.03
Herr., “The future of career counselling as an instrument of public policy”. The Career development quarterly, 52, 8–17, 2003
Kerry B. Bernes Angela D. Bardick David T. Orr “Career guidance and counselling efficacy studies: an international research agenda” Int J Educ Vocat Guid, Springer Science +Business Media B.V.:81–96, 2007
Dagley, J. C., & Salter, S. K. “Practice and research in career counselling and development—2003”, The Career Development Quarterly, 53, 99–157, 2004
Savickas, M. L., & Porfeli, E. J. Career Adapt-Abilities Scale: Construction, reliability, and measurement equivalence across 13 countries. Journal of Vocational Behavior, 80(3), 661–673, 2012
Andreas Hirschi, Domingo Valero “Career adaptability profiles and their relationship to adaptivity and adapting” Journal of Vocational Behavior 88: Elsevier, pp. 220–229, 2015
Super, D. E., & Knasel, E. G. “Career development in adulthood: Some theoretical problems and a possible solution”. British Journal of Guidance and Counselling, 9, 194–201, 1981
C.S. Krishnamoorthy, S. Rajeev, Artificial intelligence and expert systems for engineers. LLC: CRC Press; 1996.
G. A. Ansari “An Adoptive Medical Diagnosis System Using Expert System with Applications” Journal of Emerging Trends in Computing and Information Sciences, Vol. 4, No. 3 Mar 2013
L. M. Laita, G. Gonzlez-Paez, E. Roanes-Lozano, V. Maojo, L. de Ledesma. A methodology for constructing expert systems for medical diagnosis, ISMDA 2001, Crespo, J., Maojo,V., Martin, F. (Eds.), Springer-Verlag, LNCS, (2199):146–152, 2001
J. Bann; G. Irisarri; D. Kirschen; et al., “Integration of Artificial Intelligence Applications in the EMS: Issues and Solutions”, IEEE Transactions on Power Systems, Vol. 11, No. 1, pp. 475-482, Feb 1996
M. Ayman Al Ahmar “Rule Based Expert System for Selecting Software Development Methodology”, Journal of Theoretical and Applied Information Technology, 10Vol19No2, pp 143-148, 2005
A.Y. Kusiak, D. Sunderesh, S. Heragu, Expert systems and optimization. IEEE Trans Software Engineering, vol. 15, pp.1012–1017, 1989.
A. AlKhalifah, Ansari, G.A “Modeling of E-procurement System through UML using Data Mining Technique for Supplier Performance”, IEEE International Conference on Software Networking(ICSN) May 23-26, in Jiju-Islan, South Korea 2016
Manisha Jailia, Arti Tyagi “Data Mining: A Prediction for Performance Improvement in Online Learning Systems” International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 7, July 2013
Larose, D. T., “Discovering Knowledge in Data: An Introduction to Data Mining”, ISBN 0-471-66657-2, Ohn Wiley & Sons, Inc, 2005.
Romero, C., & Ventura, S. “Educational data mining: A survey from 1995 to 2005” Expert Systems with Applications, 33, 135-146, 2007
Castro, F., Vellido, A., Nebot, A., & Mugica, F “Applying data mining techniques to e-learning problems”, Studies in Computational Intelligence, 62, 183- 221, 2007
A.A. Freitas. “Data Mining and Knowledge Discovery with Evolutionary Algorithms”, Springer-Verlag, 2002
Romero, C., Ventura, S., Pechenizky, M., Baker, R. “Handbook of Educational Data Mining” Editorial Chapman and Hall/CRC Press, Taylor & Francis Group. Data Mining and Knowledge Discovery Series, 2010
Erman. LX, Scott, A.C., and London, P.E. Separating and integrating control in a rule-based tool, In Proceedings of the IEEE Workshop on Principles of Knowledge-Based Systems (Denver. Cola. Dec.), IEEE, 37-43, 1984
https://osumarion.osu.edu/assets/marion/uploads/What_Factors_Influence_a_Career_Choice.pdf [Accessed on 20-02-2017]
Tanuja Agarwala “Factors influencing career choice of management students in India” Career Development International Vol. 13 No. 4, pp. 362-376, 2008.
Parvinnia, E., et al. "Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm." Journal of King Saud University-Computer and Information Sciences 26.1, pp 1-6, 2014
Derrac, Joaquín, Salvador García, and Francisco Herrera. "Fuzzy nearest neighbor algorithms: Taxonomy, experimental analysis and prospects." Information Sciences 260, pp 98-119, 2014
Muja, Marius, and David G. Lowe. "Scalable nearest neighbor algorithms for high dimensional data" IEEE Transactions on Pattern Analysis and Machine Intelligence 36.11, pp 2227-2240, 2014