Random Articles
Reseach Article
Naive Bayes Classification Approach for Mining Life Insurance Databases for Effective Prediction of Customer Preferences over Life Insurance Products
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 51 - Number 3 |
| Year of Publication: 2012 |
| Authors: S. Balaji, S. K. Srivatsa |
10.5120/8023-0805
|
S. Balaji, S. K. Srivatsa . Naive Bayes Classification Approach for Mining Life Insurance Databases for Effective Prediction of Customer Preferences over Life Insurance Products. International Journal of Computer Applications. 51, 3 ( August 2012), 22-26. DOI=10.5120/8023-0805
Abstract
Prediction analysis is a definite need of any business sector for retaining and attracting the most valuable customers . It is considered as a major challenge facing companies in this information age. Data mining enables companies, in the context of defined business objectives, discover new knowledge, to explore, visualise and understand their data, and to identify patterns, relationships and dependencies that impact on business outcomes. The main focus of this paper concerned with Naive Bayesian classification algorithm for customer classification and prediction on Life Insurance dataset.
References
- Marisa S. Viveros,BM Research Division T. J. Watson (1996) Applying Data Mining Techniques to a Health Insurance Information System, Proceedings of the 22nd VLDB Conference Mumbai (Bombay), India.
- Kamakura, Wagner A. & Michel W. (2000). Factor analysis and missing data, Journal of Marketing Research, Vol. 37, pp. 490–498.
- Berry A. J. Michael ,&Linoff Gordon S. (2000) Mastering Data Mining: The Art and science of Customer Relationship Management ,Wiley,New Jersey.
- Saundra Glover , Patrick A Rivers , Derek A Asoh , Crystal N Piper and Keva Murph ,(2010) Data mining for health executive decision support: an imperative with a daunting future. , Health Services Management Research ,Vol. 23, Number 1 > pp. 42-46
- Jiawei Han and Micheline Kamber,Morgan, (2006),Data Mining concepts and Techniques , Kaufmann Publishers.
- Billungual report of Insurance Regulatory authority of India -2010-2011
- Zhiyuan Yao,Annika H. Holmbom,Tomas Eklund and Barbro Back,(2010),Combining Unsupervised and Supervised Data Mining Techniques for Conducting Customer Portfolio Analysis,ICDM. LNAI 6171,pp. 292-307.
- Khurana Sunayna. (2008). "Customer references in Life Insurance Industry in India", The ICFAIUniversity Journal of Services Vol. 6(3),pp. 61-68.
- Chien-Hsing Wu,, Shu-Chen Kao, Yann-Yean Su, Chuan-Chun Wu,(2005) Targeting customers via discovery knowledge for the insurance industry,Vol. 29 . pp. 291-299. Elsevier Ltd.
- Hokey Min,(2006), Developing the Profiles of Supermarket Customers through Data Mining[J],The Service Indusries Journal, Vol. 26, No. 7, pp. 747–763
- E. W. T. Ngai,L. XiuandD. C. KChau(2009),Application of data mining techniques in customer relationship management,Expert systems with applicationsVol. 36,pp. 2592-2602.
- Abrahams,A,S. Becker,A,B. Sabido,D. D. S ouza,R. Makriyiannis,G. Krasnodebski. ,(2009),Inducing a Marketing strategy for a New Pet Insurance Company using Decision trees. Expert systems with applications,Vol. 36,pp. 1914-1921.
- AnnaJurek,Danutazakrzewska,(2008),Improving Naïve Bayes models of Insurance risk by unsupervised classification,Proceedings of the International Multiconference on Computer Science and Information Technology pp. 137-144.
- Kanwal garg,Dharminder kumar and m. c. garg,(2008),Data mining techniques for identifying the customer behavior of investment in life insurance sector in india,International journal information technology and knowledge management,Vol. 1,pp. 51-56.
- Yongqiang chen,Leifang Hu,(2005),Study on data mining in CRM system based on Insurance Trade,Proceedings of International conference on Emerging trends in Computers,. pp. 839-842.
- M. Staudt,J-U. Kietz and U. Reimer,(1998),A data mining support environment and its application on Insurance data,American Journal for Aritifical Intelligence,pp. 15-19.
- Young Moon Chae , Seung Hee Ho , Kyoung Won Cho , Dong Ha Lee and Sun Ha Ji,(2001),Data mining approach to policy analysis in a health insurance domain ,International Journal of Medical Informatics,vol. 62 ,pp. 103–111.
- Young Moon Chaea, Dong Ha Leeb, Hwa Young Kima, Tae Soo Kima , Tae Min Songc(2004),Mining time dependency patterns in a Health Insurance Domain,International journal of Medical informatics,Vol. 99. pp. 1545-1555.
- Long WJ, Griffith JL, Selker HP, and D'Agostino RB. (1993), A comparison of logistic regression to decision-tree induction in a medical domain. Comp and Biomed Res Vol 26: 74-97.
Index Terms
Keywords