Classification and prediction of academic talent using data mining techniques

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6276 LNAI, Issue PART 1, 2010, Pages 491-500

  Jantan, Hamidah ^a   Hamdan, Abdul Razak ^b   Othman, Zulaiha Ali ^b  

^a UNIVERSITI TEKNOLOGI MARA   (Malaysia)

^b UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Academic talent; Classification; Data mining (DM); Prediction

Indexed keywords

ACADEMIC TALENT; CLASSIFICATION; CLASSIFICATION MODELS; CLASSIFICATION TECHNIQUE; DATA MINING TECHNIQUES; HIGHER EDUCATION INSTITUTIONS; HUMAN CAPITALS; HUMAN RESOURCES; ISSUES AND CHALLENGES; POTENTIAL TECHNIQUES; PREDICTION; PREDICTION TECHNIQUES; TALENT MANAGEMENT;

DATA MINING; EDUCATION; FORECASTING; HUMAN RESOURCE MANAGEMENT; KNOWLEDGE BASED SYSTEMS; SOCIETIES AND INSTITUTIONS;

CLASSIFICATION (OF INFORMATION);

EID: 78449249359     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15387-7_53     Document Type: Conference Paper

References (17)

1. Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann Publisher, San Francisco (2006)
2. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Publisher, San Francisco (2005)
3. Chien, C.F., Chen, L.F.: Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry. Expert Systems and Applications 34, 380-390 (2008)
4. Wang, H., Wang, S.: A knowledge management approach to data mining process for business intelligence. Industrial Management & Data Systems 108, 622-634 (2008)
5. Ranjan, J.: Data Mining Techniques for better decisions in Human Resource Management Systems. International Journal of Business Information Systems 3, 464-481 (2008)
6. Cubbingham, I.: Talent Management: Making it real. Development and Learning in Organizations 21, 4-6 (2007)
7. Cappelli, P.: Talent Management for the Twenty-First Century, http://www.hbr.org
8. A TP Track Research Report Talent Management: A State of the Art. Tower Perrin HR Services (2005)
9. Jantan, H., Hamdan, A.R., Othman, Z.A.: Knowledge Discovery Techniques for Talent Forecasting in Human Resource Application. In: World Academy of Science, Engineering and Technology, Penang, Malaysia, pp. 803-811 (2009)
10. Huang, M.J., Tsou, Y.L., Lee, S.C.: Integrating fuzzy data mining and fuzzy artificial neural networks for discovering implicit knowledge. Knowledge-Based Systems 19, 396-403 (2006)
11. Chien, C.F., Chen, L.F.: Using Rough Set Theory to Recruit and Retain High-Potential Talents for Semiconductor Manufacturing. IEEE Transactions on Semiconductor Manufacturing 20, 528-541 (2007)
12. Tung, K.Y., Huang, I.C., Chen, S.L., Shih, C.T.: Mining the Generation Xer's job attitudes by artificial neural network and decision tree-empirical evidence in Taiwan. Expert Systems and Applications 29, 783-794 (2005)
13. Chen, K.K., Chen, M.Y., Wu, H.J., Lee, Y.L.: Constructing a Web-based Employee Training Expert System with Data Mining Approach. In: The 9th IEEE International Conference on E-Commerce Technology and The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC-EEE 2007 (2007)
14. Lynne, M.: Talent Management Value Imperatives: Strategies for Execution. In: The Conference Board (2005)
15. CHINA UPDATE. HR News for Your Organization: The Tower Perrin Asia Talent Management Study, http://www.towersperrin.com
16. Jantan, H., Hamdan, A.R., Othman, Z.A.: Data Mining Techniques for Performance Prediction in Human Resource Application. In: 1st Seminar on Data Mining and Optimization, pp. 41-49. CAIT UKM, Selangor (2008)
17. Tso, G.K.F., Yau, K.K.W.: Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks. Energy 32, 1761-1768 (2007)