3. 9– File lưu trữ một số mẫu khách hàng mục tiêu
C.1 thị thời gian chạy củ a2 giải thuật Johnson và chuỗi bit
0 500 1,000 1,500 2,000 2,500 3,000 3,500 0 1,000,000 2,000,000 3,000,000 Ti m e ( u n it : s e co n d ) Number of Propositions in f Johnson Strategy 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0 5,000,000 10,000,000 15,000,000 Ti m e ( u n it : s e co n d ) Number of Bit-chains
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TÀI LIỆU THAM KHẢO Tiếng Anh
1. Thanh-Trung Nguyen, Viet-Long Huu Nguyen, and Phi-Khu Nguyen – Identifying Customer Characteristics By Using Rough Set Theory With A New Algorithm And Posterior Probabilities – 2012 Fourth International Conference on Computational and Information Sciences.
2. Thanh-Trung Nguyen, Viet-Long Huu Nguyen and Phi-Khu Nguyen – A Bit-Chain Based Algorithm for Problem of Attribute Reduction – Intelligent Information and Database Systems, Lecture Notes in Computer Science, 2012.
3. K. Khalili Damghani, M. T. Taghavifard, R. Tavakkoli Moghaddam – Decision Making Under Uncertain and Risky Situations – Enterprise Risk Management Symposium Monograph Society of Actuaries - Schaumburg, Illinois, 2009.
4. Ali Ahmady – Identifying Users’ Characteristics Critical to Product Selection: Using Rough Set Theory – Proceedings of the 5th Annual GRASP Symposium, Wichita State University, 2009.
5. M. Kartiwi – Customer Characteristics’ Influence on Online Trust in Developing Countries: An Examination of Confidence Level – Managing Information in the Digital Economy: Issues & Solutions - Proceedings of the 6th International Business Information Management Association (IBIMA) Conference, Bonn, 19-21 June 2006. 6. Amy Wong & Alison Dean – The Effects Of Store And Customer Characteristics On
Value And Loyalty – ANZMAC 2005 Conference: Services Marketing, 2005.
7. Nicolas Glady and Christophe Croux – Predicting Customer Wallet without Survey Data – Journal of Services Research, Vol. 11, Issue 3, p. 219-231, Feb 2009.
8. J. Jeffrey Inman, Russell S. Winer, & Rosellina Ferraro – The Interplay Among Category Characteristics, Customer Characteristics, and Customer Activities on In- Store Decision Making – Journal of Marketing, Vol. 73, p. 19–29, September 2009. 9. James J.H. Liou, Gwo-Hshiung Tzeng – A Dominance-based Rough Set Approach to
customer behavior in the airline market – Information Sciences, 2010.
10.Saiful Hafizah Jaaman – A Predictive Model Construction Applying Rough Set Methodology for Malaysian Stock Market Returns – International Research Journal of Finance and Economics, ISSN 1450-2887 Issue 30 (2009)
11.Elliot A. Tanis, Robert V. Hogg – A brief course in Mathematical Statistics – Pearson Prentice Hall, Inc. 2008.
Khóa luận tốt nghiệp Cử nhân tài năng 02 – Khoa học máy tính Trang 80
13.J. Han and M. Kamber – Data Mining: Concepts and Techniques, Second Edition – Morgan Kaufmann, 2006.
14.Chein-Shung Hwang, Yi-Ching Su, and Kuo-Cheng Tseng – Using Genetic Algorithms for Personalized Recommendation – Computational Collective Intelligence. Technologies and Applications, Second International Conference, ICCCI 2010, Kaohsiung, Taiwan, November 10-12, 2010, Proceedings, Part II.
15.Mark L. Berenson, David M. Levine, Timothy C. Krehbiel – Basic Business Statistics: Concepts and Applications (8th edition), Chapter 17 – Prentice Hall, Inc. 2002.
16.Kenneth H. Rosen – Discrete Mathematics and Its Applications, 6th Edition – McGraw-Hill, 2007
17.D. S. Johnson – Approximation algorithms for combinatorial problems – Proc. Fifth Annual ACM Symposium on Theory of Computing, pp. 38-49, 1974.
18.Hung Son Nguyen, Andrzej Skowron – Boolean Reasoning for Feature Extraction Problems – Lecture Notes in Computer Science, 1997, Volume 1325/1997, 117-126. 19.Nizar Sakr, Fawaz A. Alsulaiman, Julio J. Valdés, Abdulmotaleb El Saddik, Nicolas
D. Georganas – Feature Selection in Haptic-based Handwritten Signatures Using Rough Sets – Fuzzy Systems, 2010 IEEE International Conference.
20.Anany Levitin – Introduction to The Design & Analysis of Algorithms, 2nd Edition – Pearson Education, Inc. 2007.
21.E.W.T. Ngai, Li Xiu, D.C.K. Chau – Application of data mining techniques in customer relationship management: A literature review and classification – Expert Systems with Applications, 2009.
22.Zdzisław Pawlak – Rough Sets – The Tarragona University seminar on Formal Languages and Rough Sets in August 2003.
23.Paul E. Green – Bayesian Classification Procedures in Analyzing Customer Characteristics – Journal of Marketing Research, 1964.
Tiếng Việt
24.Cao Hào Thi – Giới thiệu về thống kê – Fulbright Economics Teaching Program OpenCourseWare, 2011.
25.PGS. TS. Đỗ Phúc – Giáo trình Khai thác dữ liệu – Nhà xuất bản Đại học Quốc Gia thành phố Hồ Chí Minh, 2008.
26.Trần Hạnh Nhi, Dương Anh Đức – Cấu trúc dữ liệu và giải thuật – Nhà xuất bản Đại học Quốc Gia thành phố Hồ Chí Minh, 2007.