DATA MINING AND ITS EFFICACY IN KNOWLEDGE MANAGEMENT WITH RESPECT TO HRIS APPLICATION

Authors

  • Ms. Tripti Chopra Research Scholar CPUR, Kota, INDIA
  • Dr. Shine David Assistant Professor, IMS Indore, INDIA

DOI:

https://doi.org/10.29121/granthaalayah.v4.i9.2016.2535

Keywords:

Data mining, Knowledge management, HRIS

Abstract [English]

Industries are constantly trying to stay competitive by retaining its reputation in the market in which it is operating. Due to Globalization companies have to rethink their strategies and practices. A company’s strategy highly depends upon the use of application and the utilization of resources. Amidst all these HR factors tend to play a potential role in determining the effectiveness and competitiveness of an organization. HRIS is generally considered as managing people practices using IT enabled services. Thus it is a task of HRIS to cater to the needs of knowledge management .Knowledge management involves the practices which are utilized to get the right people at right time to train them and finally appraising their performance and reward them. This helps in keeping employees satisfied and happy. When the performance of an employee is evaluated a number of techniques are used to mine the utmost knowledge out of them. This is how HRIS is connected to Knowledge management. This empirical study is an effort in knowing the efficacy of data mining techniques in knowledge management and application of HRIS. The major focus of study is to know about the data base of employees for predicting the performance of employees and adopt a knowledge management strategy and the efficacy of data mining in doing so.

Downloads

Download data is not yet available.

References

Berry, M. J. A., &Linnof, G, Data mining Techniques, New York: Wiley, (1997).

Agrawal, R., Imielinski, T., and Swami, A., 1993. Mining association rules between sets of items in large databases .In Proceedings of the ACM SIGMOD International Conference on Management of Data (ACM SIGMOD ‟93), pages 207 – 216, Washington, USA. DOI: https://doi.org/10.1145/170036.170072

Agrawal, R. and Srikant, R., 1994.Fast algorithms for mining association rules. In Proceedings of the 20th International Conference on Very Large Databases (VLDB ‟94), Santiago, Chile

Agrawal, R. and Shim, K., 1996.Developing tightly coupled data mining applications on a relational database system. In Proceedings of the 2nd International Conference on Knowledge Discovery in Databases and Data Mining (KDD ‟96), Portland, Oregon, USA

Data Mining definition Available at http://www.gartner.com/it-glossary/data-mining/ Gupta, A. and McDaniel, J. (2002), ‘Creating competitive advantage by effectively managing knowledge management, Journal of knowledge Management Practice, Vol 3, No 2; pp40-49.

Jiawei, H (2003) Data Mining: Current status and Research Directions ; School of Computing Science ,Simon Fraser University , March Burnaby , B.C. Canada ;Augusthttp://www.cs.sfu.ca/~han

J. Han and M. Kamber, Data Mining: Concepts and Techniques. San Francisco: Morgan Kaufmann Publisher, 2006.

Hariharan, A. (2002), Knowledge Management: A strategic Tool, Journalof knowledge Management Practice, Vol. 3; No. 3; pp 50-59

Jantan, H., Hamdan, A. R., & Othman, Z. A., Human Talent Prediction in HRM using C4.5 Classification Algorithm, (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 08, 2010, 2526-2534.

Berson, A., Smith, S.J. &Thearling, K. (1999).Building Data Mining Applications for CRM. New York: McGraw-Hill.

Ranjan, J. (2008). Data Mining Techniques for better decisions in Human Resource Management Systems .International Journal of Business Information Systems, 3(5), 464- 481. DOI: https://doi.org/10.1504/IJBIS.2008.018597

Chien, C. F., & Chen, L. F. (2008). Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry .Expert Systems and Applications, 34(1), 380-290. DOI: https://doi.org/10.1016/j.eswa.2006.09.003

Scarbrough, H. and Swan, J. (2001) „Explaining the diffusion of knowledge management: The role of fashion‟, British Journal of Management, 12, 3-12 Wiig, K. M. (September 1997) ‘Knowledge management: An introduction and Perspective’ The Journal of knowledgemanagement, Vol 1, No 1 pp 6-14.

Mena J. (1999), ‘Data Mining Your Website’, dpDigital Press, ISBN: 1- 55558-222-2, The United States of America.

Petersen, N.J. and Poulfelt, F. (2002) Knowlegde Management in Action: A Study of Knowledge Management in Management Consultancies, Working Paper 1-2002, Kaupmannahöfn: Copenhagen Business School.

J. Han and M. Kamber, Data Mining: Concepts and Techniques. San Francisco: Morgan Kaufmann Publisher, 2006.

Dawei, J. (2011). The Application of Date Mining in Knowledge Management.2011 International Conference on Management of e-Commerce and e-Government, IEEE Computer Society, 7-9. doi: 10.1109/ICMeCG.2011.58 DOI: https://doi.org/10.1109/ICMeCG.2011.58

Fayyad, U., Piatetsky-Shapiro, G. & Smyth, P. (1996). From Data Mining to Knowledge Discovery in Databases.AI Magazine, 17(3), 37-54

Liao, S. (2003). Knowledge management technologies and applications-literature review from 1995 to 2002. Expert Systems with Applications, 25, 155-164. doi:10.1016/S0957-4174(03)000435

Laakso-Manninen, R. &Viitala, R. 2007. Competence management and Human Resource Development. A theoretical framework for understanding the practices of modern Finnish organizations. Helsinki. Edita.

Hahn, J. &Subramani, M. 2000. A Framework of Knowledge Management Systems: Issues and Challenges for Theory and Practice. ICIS 2000 Proceedings Paper28.

http://aisel.aisnet.org/icis2000/28

Nonaka, Ikujiro (1991). "The knowledge creating company". Harvard Business Review 69 (6 Nov–Dec): 96–104. http://hbr.harvardbusiness.org/2007/07/the-knowledge-creating-company/es.

Addicott, Rachael; McGivern, Gerry; Ferlie, Ewan (2006). "Networks, Organizational Learning and Knowledge Management: NHS Cancer Networks". Public Money & Management 26 (2): 87–94. doi:10.1111/j.1467-9302.2006.00506.

Wright, Kirby (2005). "Personal knowledge management: supporting individual knowledge worker performance". Knowledge Management Research and Practice 3 (3): 156–165. doi:10.1057/palgrave.kmrp.8500061 DOI: https://doi.org/10.1057/palgrave.kmrp.8500061

Downloads

Published

2016-09-30

How to Cite

Chopra, T., & David, S. (2016). DATA MINING AND ITS EFFICACY IN KNOWLEDGE MANAGEMENT WITH RESPECT TO HRIS APPLICATION. International Journal of Research -GRANTHAALAYAH, 4(9), 55–62. https://doi.org/10.29121/granthaalayah.v4.i9.2016.2535