-
2
-
-
33745800994
-
Sequential conditional generalized iterative scaling
-
J. Goodman. Sequential conditional generalized iterative scaling. In Proceedings of NAACL-2002, 2002.
-
(2002)
Proceedings of NAACL-2002
-
-
Goodman, J.1
-
8
-
-
84958652227
-
Integrating web usage and content mining for more effective personalization
-
Lecture Notes in Computer Science (LNCS) 1875. Springer, September
-
B. Mobasher, H. Dai, T. Luo, Y. Sun, and J. Zhu. Integrating web usage and content mining for more effective personalization. In E-Commerce and Web Technologies: Proceedings of the EC- WEB 2000 Conference, Lecture Notes in Computer Science (LNCS) 1875, pages 165-176. Springer, September 2000.
-
(2000)
E-commerce and Web Technologies: Proceedings of the EC- WEB 2000 Conference
, pp. 165-176
-
-
Mobasher, B.1
Dai, H.2
Luo, T.3
Sun, Y.4
Zhu, J.5
-
11
-
-
10944232629
-
Collaborative filtering with maximum entropy
-
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.
-
(2004)
IEEE Intelligent Systems, Special Issue on Mining the Web Actionable Knowledge
-
-
Pavlov, D.1
Manavoglu, E.2
Pennock, D.3
Giles, C.4
-
13
-
-
0033325071
-
A framework for collaborative, content-based and demographic filtering
-
M. Pazzani. A framework for collaborative, content-based and demographic filtering. Artificial Intelligence Review, 13(5-6):393-408, 1999.
-
(1999)
Artificial Intelligence Review
, vol.13
, Issue.5-6
, pp. 393-408
-
-
Pazzani, M.1
-
14
-
-
0012253296
-
Probabilistic models for unified collaborative and content-based recommendation in sparse-data environments
-
Seattle, WA
-
A. Popescul, L. Ungar, D. Pennock, and S. Lawrence. Probabilistic models for unified collaborative and content-based recommendation in sparse-data environments. In Proceedings of 17th UAI, Seattle, WA, 2001.
-
(2001)
Proceedings of 17th UAI
-
-
Popescul, A.1
Ungar, L.2
Pennock, D.3
Lawrence, S.4
-
16
-
-
85052617391
-
Item-based collaborative filtering recommendation algorithms
-
Hong Kong, May
-
B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International WWW Conference, Hong Kong, May 2001.
-
(2001)
Proceedings of the 10th International WWW Conference
-
-
Sarwar, B.1
Karypis, G.2
Konstan, J.3
Riedl, J.4
-
17
-
-
2342586046
-
Collaborative ensembling learning: Combining collaborative and content-based information filtering
-
K. Yu, A. Schwaighofer, V. Tresp, W. Ma, and H. Zhang. Collaborative ensembling learning: Combining collaborative and content-based information filtering. In Proceedings of 19th UAI, 2003.
-
(2003)
Proceedings of 19th UAI
-
-
Yu, K.1
Schwaighofer, A.2
Tresp, V.3
Ma, W.4
Zhang, H.5
|