Rough Set Theory in analyzing the attributes of combination values for the insurance market

Expert Systems with Applications

Volumn 32, Issue 1, 2007, Pages 56-64

  Shyng, Jhieh Yu ^a   Wang, Fang Kuo ^b,c   Tzeng, Gwo Hshiung ^d   Wu, Kun Shan ^c  

^a LAN YANG INSTITUTE OF TECHNOLOGY   (Taiwan)

^b MING CHUAN UNIVERSITY   (Taiwan)

^c TAMKANG UNIVERSITY   (Taiwan)

^d KAINAN UNIVERSITY   (Taiwan)

Author keywords

Combination values; Decision rule; Expert knowledge; Insurance marketing; Rough Set Theory

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL METHODS; CUSTOMER SATISFACTION; DATA REDUCTION; DECISION THEORY; EXPERT SYSTEMS; INDUSTRIAL INSURANCE; MARKETING;

COMBINATION VALUES; DECISION RULE; INSURANCE MARKETING;

ROUGH SET THEORY;

EID: 33748195464     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2005.11.002     Document Type: Article

References (25)

1. Azibi R., and Vanderpooten D. Construction of rule-based assignment models. European Journal of Operational Research 138 2 (2002) 274-293
2. Beynon M.J., and Peel M.J. Variable precision rough set theory and data discrimination: An application to corporate failure prediction. OMEGA: the International Journal of Management Science 29 6 (2001) 561-576
3. Chan C.C. A rough set approach to attribute generalization in data mining. Journal of Information Sciences 107 1-4 (1998) 169-176
4. Dimitras A.I., Slowinski R., Susmaga R., and Zopounidis C. Business failure prediction using rough sets. European Journal of Operational Research 114 2 (1999) 263-280
5. Goh C., and Law R. Incorporating the rough sets theory into travel demand analysis. Tourism Management 24 5 (2003) 511-517
6. Greco S., Matarazzo B., and Slowinski R. Rough sets theory for multicriteria decision analysis. European Journal of Operational Research 129 1 (2001) 1-47
7. Hassan, Y., & Tazaki, E. (2001). Rule extraction based on rough set theory combined with genetic programming and its application to medical data analysis. In 7th Australian and New Zealand intelligent information system conference, Perth, Australia.
8. Hennig-Thurau T., and Klee A. The impact of customer satisfaction and relationship quality on customer retention: A critical reassessment and model development. Psychology & Marketing 14 8 (1997) 737-764
9. Hu Y.C., Chen R.S., and Tzeng G.H. Finding fuzzy classification rules using data mining techniques. Pattern Recognition Letters 24 1-3 (2003) 509-519
10. Huang J.J., Ong C.S., and Tzeng G.H. Building credit scoring models using genetic programming. Expert Systems with Applications 29 1 (2005) 41-47
11. Inuiguchi, M. (2004). Generalizations of rough sets: From crisp to fuzzy cases. Rough sets and current trends in computing by Shusaku Tsumoto, Roman Slowinski, Jan Komoroski, Jerzy W. Grzymala-Busse (Eds.), Lecture Notes in Artificial Intelligence (LNAI), 3066(1), 26-37.
12. Jackson A.G., Leclair S.R., Ohmer M.C., Ziarko W., and Al-kamhwi H. Rough sets applied to materials data. ACTA Material 44 11 (1996) 4475-4484
13. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2003). A study of the effect of consumer trust on consumer expectations and satisfaction: The Korean experience. In ACM international conference proceeding series: Proceedings of the 5th international conference on electronic commerce, Pittsburgh, pp. 310-315.
14. Li R., and Wang Z.O. Mining classification rules using rough sets a nd neural networks. European Journal of Operational Research 157 2 (2004) 439-448
15. Pawlak Z. Rough sets. International Journal of Computer and Information Science 11 5 (1982) 341-356
16. Pawlak Z. Rough classification. International Journal of Man-Machine Studies 20 5 (1984) 469-483
17. Pawlak Z. Rough sets, decision algorithms and Bayes' theorem. European Journal of Operational Research 136 1 (2002) 181-189
18. Pawlak, Z. (2004). Decision networks. Rough Sets and Current Trends in Computing by Shusaku Tsumoto, Roman Slowinski, Jan Komoroski, Jerzy W. Grzymala-Busse (Eds.), Lecture Notes in Artificial Intelligence (LNAI), 3066(1), 1-7.
19. Polkowski, L. (2004). Toward rough set foundations, mereological approach. Rough Sets and Current Trends in Computing by Shusaku Tsumoto, Roman Slowinski, Jan Komoroski, Jerzy W. Grzymala-Busse (Eds.), Lecture Notes in Artificial Intelligence (LNAI), 3066(1), 8-25.
20. Quafafou M. α-RST: A generalization of rough set theory. Information Sciences 124 4 (2000) 301-316
21. Swiniarski R.W., and Skowron A. Rough set methods in feature selection and recognition. Pattern Recognition Letters 24 6 (2003) 833-849
22. Walczak B., and Massart D.L. Tutorial rough sets theory. Chemometrics and Intelligent Laboratory Systems 47 1 (1999) 1-16
23. Witlox F., and Tindemans H. The application of rough sets analysis in activity-based modeling, opportunities and constraints. Expert Systems with Application 27 2 (2004) 171-180
24. Zadeh L.A. Fuzzy sets. Information and Control 8 3 (1965) 338-353
25. Zhai L.Y., Khoo L.P., and Fok S.C. Feature extraction using rough set theory and genetic algorithms an application for the simplification of product quality evaluation. Computers & Industrial Engineering 43 4 (2002) 661-676