1. Trang chủ
  2. » Luận Văn - Báo Cáo

Hệ thống hỗ trợ tư vấn trong thương mại điện tử

68 503 1

Đang tải... (xem toàn văn)

Tài liệu hạn chế xem trước, để xem đầy đủ mời bạn chọn Tải xuống

THÔNG TIN TÀI LIỆU

Thông tin cơ bản

Định dạng
Số trang 68
Dung lượng 2,09 MB

Nội dung

Ngày đăng: 25/03/2015, 09:41

Nguồn tham khảo

Tài liệu tham khảo Loại Chi tiết
5. Basu, C., H. Hirsh, and W. Cohen. “Recommendation as classification: Using social and content-based information in recommendation”. In Recommender Systems. Papers from 1998 Workshop. Technical Report WS-98- 08. AAAI Press, 1998 Sách, tạp chí
Tiêu đề: Recommendation as classification: "Using social and content-based information in recommendation”
7. Billsus, D. and M. Pazzani. “Learning collaborative information filters”. In International Conference on Machine Learning, Morgan Kaufmann Publishers, 1998 Sách, tạp chí
Tiêu đề: Learning collaborative information filters”
8. Breese, J. S., D. Heckerman, and C. Kadie. “Empirical analysis of predictive algorithms for collaborative filtering”. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, 1998 Sách, tạp chí
Tiêu đề: Empirical analysis of predictive algorithms for collaborative filtering”
9. Chien, Y-H. and E. I. George. “A bayesian model for collaborative filtering”. In Proc. of the 7 th International Workshop on Artificial Intelligence and Statistics, 1999 Sách, tạp chí
Tiêu đề: “A bayesian model for collaborative filtering”
10. Chihiro Ono, Yoichi Motomura, Hideki Asoh, “A Study of Probabilistic Models for Integrating Collaborative and Content-based Recommendation,”p162-168, Multidisciplinary IJCAI-05 Workshop on Advances in Preference Handling Ronen Brafman and Ulrich Junker (organizers) July 31 - August 1, 2005 Edinburgh, Scotland Sách, tạp chí
Tiêu đề: A Study of Probabilistic Models for Integrating Collaborative and Content-based Recommendation,”
11. Claypool, M., A. Gokhale, T. Miranda, P. Murnikov, D. Netes, and M. Sartin. “Combining content-based and collaborative filters in an online newspaper”. In ACM SIGIR'99. Workshop on Recommender Systems:Algorithms and Evaluation, August 1999 Sách, tạp chí
Tiêu đề: “Combining content-based and collaborative filters in an online newspaper”
12. D. Pavlov, E. Manavoglu, D. Pennock, and C. Giles. “Collaborative filtering with maximum entropy”. IEEE Intelligent Systems, Special Issue on Mining the Web Actionable Knowledge, 2004 Sách, tạp chí
Tiêu đề: Collaborative filtering with maximum entropy
13. G.Adomavicius, A.Tuzhilin. Towards the Next Generation of Recommender Systems:A Survey of the State-of-the-Art and Possible Extensions, IEEE Transactions on Knowledge and Data Engineering, 2005.A4. Grouplens home page http://www.grouplens.org 14. IMDB home page http://www.imdb.com/ Sách, tạp chí
Tiêu đề: Towards the Next Generation of Recommender Systems:A Survey of the State-of-the-Art and Possible Extensions
15. Janusz Sobecki, “Implementations of Web-based Recommender Systems Using Hybrid Methods”, International Journal of Computer Science &Applications Vol. 3 Issue 3, pp 52-64 Sách, tạp chí
Tiêu đề: “Implementations of Web-based Recommender Systems Using Hybrid Methods”
16. J. Salter and N. Antonopoulos, “CinemaScreen recommender agent: Combining collaborative and content-based filtering,” IEEE Intell. Syst.,vol. 21, no. 1, pp. 35–41, Jan./Feb. 2006 Sách, tạp chí
Tiêu đề: “CinemaScreen recommender agent: "Combining collaborative and content-based filtering,” IEEE Intell. Syst
17. J.Wang, A. Vries, and M. Reinders, “Unifying user-based and item-based collaborative filtering approaches by similarity fusion,” in Proc. SIGIR Conf., 2006, pp. 501–508 Sách, tạp chí
Tiêu đề: “Unifying user-based and item-based collaborative filtering approaches by similarity fusion,”
19. Linden, G., B. Smith, and J. York. “Amazon.com Recommendations: Item- to-Item Collaborative Filtering”. IEEE Internet Computing, Jan-Feb/ 2003 Sách, tạp chí
Tiêu đề: “Amazon.com Recommendations: Item-to-Item Collaborative Filtering”
20. Mark van Setten, Mettina Veenstra, Anton Nijholt, Betsy van Dijk. “Case- Based Reasoning as a Prediction Strategy for Hybrid Recommender Systems” Sách, tạp chí
Tiêu đề: “Case-Based Reasoning as a Prediction Strategy for Hybrid Recommender Systems
21. Mooney, R. J., P. N. Bennett, and L. Roy. “Book recommending using text categorization with extracted information”. In Recommender Systems. Papers from 1998 Workshop. Technical Report WS-98-08. AAAI Press, 1998 Sách, tạp chí
Tiêu đề: Book recommending using text categorization with extracted information”
23. M.Vozalis, K.G.Margaritis, “Collaborative filtering enhanced by demographic correlation,” in: Proceedings of the AIAI Symposium on Professional Practice in AI, Part of the 18th World Computer Congress, Toulouse, France, 2004, pp. 393-402 Sách, tạp chí
Tiêu đề: Collaborative filtering enhanced by demographic correlation
24. Pazzani, M. A framework for collaborative, content-based and demographic filtering. Artificial Intelligence Review, pages 393-408, December 1999 Sách, tạp chí
Tiêu đề: A framework for collaborative, content-based and demographic filtering
25. Pazzani M., & Billsus, D. (1997). “Learning and Revising User Profiles: The identification of interesting web sites”. Machine Learning 27, p313-331 Sách, tạp chí
Tiêu đề: Learning and Revising User Profiles: "The identification of interesting web sites”". Machine Learning" 27
Tác giả: Pazzani M., & Billsus, D
Năm: 1997
26. P. Li, S. Yamada, “A movie recommender system based on inductive learning,” in: Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems, vol. 1, December 2004, pp. 318-323 Sách, tạp chí
Tiêu đề: “A movie recommender system based on inductive learning,”
1. ACM Homepage http://recsys.acm.org/2010 2. Amazon home page http://www.amazon.com/ Link
18. Library for Support Vector Machines home page: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Link

TỪ KHÓA LIÊN QUAN

TRÍCH ĐOẠN

TÀI LIỆU CÙNG NGƯỜI DÙNG

TÀI LIỆU LIÊN QUAN