Thị thời gian chạy củ a2 giải thuật Johnson và chuỗi bit

Một phần của tài liệu XÁC ĐỊNH ĐẶC TRƯNG KHÁCH HÀNG DỰA TRÊN TẬP THÔ (Trang 80)

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.

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