-
1
-
-
33750367864
-
Learning user interaction models for predicting web search result preferences
-
New York, NY, USA, ACM Press
-
E. Agichtein, E. Brill, S. Dumais, and R. Ragno. Learning user interaction models for predicting web search result preferences. In Proceedings of ACM SIGIR 2006, pages 3-10, New York, NY, USA, 2006. ACM Press.
-
(2006)
Proceedings of ACM SIGIR 2006
, pp. 3-10
-
-
Agichtein, E.1
Brill, E.2
Dumais, S.3
Ragno, R.4
-
2
-
-
33746043842
-
Ranking tournaments
-
DOI 10.1137/050623905
-
N. Alon. Ranking tournaments. SIAM J. Discret. Math., 20 (1): 137-142, 2006. (Pubitemid 46352091)
-
(2006)
SIAM Journal on Discrete Mathematics
, vol.20
, Issue.1
, pp. 137-142
-
-
Alon, N.1
-
3
-
-
70049116439
-
Ranking as function approximation
-
C. Burges. Ranking as function approximation. Algorithms for Approximation, pages 3-18, 2006.
-
(2006)
Algorithms for Approximation
, pp. 3-18
-
-
Burges, C.1
-
4
-
-
31844446958
-
Learning to rank using gradient descent
-
C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, and G. Hullender. Learning to rank using gradient descent. In Proceedings of the 22nd international conference on Machine learning, pages 89-96, 2005.
-
(2005)
Proceedings of the 22nd International Conference on Machine Learning
, pp. 89-96
-
-
Burges, C.1
Shaked, T.2
Renshaw, E.3
Lazier, A.4
Deeds, M.5
Hamilton, N.6
Hullender, G.7
-
5
-
-
34547987951
-
Learning to rank: From pairwise approach to listwise approach
-
New York, NY, USA, ACM
-
Z. Cao, T. Qin, T.-Y. Liu, M.-F. Tsai, and H. Li. Learning to rank: from pairwise approach to listwise approach. In ICML '07: Proceedings of the 24th international conference on Machine learning, pages 129-136, New York, NY, USA, 2007. ACM.
-
(2007)
ICML '07: Proceedings of the 24th International Conference on Machine Learning
, pp. 129-136
-
-
Cao, Z.1
Qin, T.2
Liu, T.-Y.3
Tsai, M.-F.4
Li, H.5
-
7
-
-
84865624822
-
A dynamic bayesian network click model for web search ranking
-
New York, NY, USA, ACM
-
O. Chapelle and Y. Zhang. A dynamic bayesian network click model for web search ranking. In WWW '09: Proceedings of the 18th international conference on World wide web, pages 1-10, New York, NY, USA, 2009. ACM.
-
(2009)
WWW '09: Proceedings of the 18th International Conference on World Wide Web
, pp. 1-10
-
-
Chapelle, O.1
Zhang, Y.2
-
9
-
-
42549140738
-
An experimental comparison of click position-bias models
-
N. Craswell, O. Zoeter, M. Taylor, and B. Ramsey. An experimental comparison of click position-bias models. In WSDM'08: Proceedings of the international conference on Web search and web data mining, pages 87-94, 2008.
-
(2008)
WSDM'08: Proceedings of the International Conference on Web Search and Web Data Mining
, pp. 87-94
-
-
Craswell, N.1
Zoeter, O.2
Taylor, M.3
Ramsey, B.4
-
10
-
-
33745774624
-
Regularizing ad hoc retrieval scores
-
New York, NY, USA, ACM
-
F. Diaz. Regularizing ad hoc retrieval scores. In CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management, pages 672-679, New York, NY, USA, 2005. ACM.
-
(2005)
CIKM '05: Proceedings of the 14th ACM International Conference on Information and Knowledge Management
, pp. 672-679
-
-
Diaz, F.1
-
13
-
-
0035470889
-
Greedy function approximation: A gradient boosting machine
-
J. Friedman. Greedy function approximation: a gradient boosting machine. Ann. Statist., 29: 1189-1232, 2001. (Pubitemid 33405972)
-
(2001)
Annals of Statistics
, vol.29
, Issue.5
, pp. 1189-1232
-
-
Friedman, J.H.1
-
15
-
-
52949143827
-
Label ranking by learning pairwise preferences
-
18971916
-
E. Hüllermeier, J. Fürnkranz, W. Cheng, and K. Brinker. Label ranking by learning pairwise preferences. Artif. Intell., 172 (16-17):1897-1916, 2008.
-
(2008)
Artif. Intell.
, vol.172
, pp. 1617
-
-
Hüllermeier, E.1
Fürnkranz, J.2
Cheng, W.3
Brinker, K.4
-
17
-
-
72449125706
-
Global ranking by exploiting user clicks
-
New York, NY, USA, ACM
-
S. Ji, K. Zhou, C. Liao, Z. Zheng, G.-R. Xue, O. Chapelle, G. Sun, and H. Zha. Global ranking by exploiting user clicks. In SIGIR '09: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, pages 35-42, New York, NY, USA, 2009. ACM.
-
(2009)
SIGIR '09: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval
, pp. 35-42
-
-
Ji, S.1
Zhou, K.2
Liao, C.3
Zheng, Z.4
Xue, G.-R.5
Chapelle, O.6
Sun, G.7
Zha, H.8
-
18
-
-
0242456822
-
Optimizing search engines using clickthrough data
-
New York, NY, USA, ACM Press
-
T. Joachims. Optimizing search engines using clickthrough data. In KDD '02: Proceedings of the eighth ACM SIGKDD, pages 133-142, New York, NY, USA, 2002. ACM Press.
-
(2002)
KDD '02: Proceedings of the Eighth ACM SIGKDD
, pp. 133-142
-
-
Joachims, T.1
-
19
-
-
84885665252
-
Accurately interpreting clickthrough data as implicit feedback
-
New York, NY, USA, ACM Press
-
T. Joachims, L. Granka, B. Pan, H. Hembrooke, and G. Gay. Accurately interpreting clickthrough data as implicit feedback. In Proceedings of ACM SIGIR 2005, pages 154-161, New York, NY, USA, 2005. ACM Press.
-
(2005)
Proceedings of ACM SIGIR 2005
, pp. 154-161
-
-
Joachims, T.1
Granka, L.2
Pan, B.3
Hembrooke, H.4
Gay, G.5
-
20
-
-
34247882698
-
Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search
-
T. Joachims, L. Granka, B. Pan, H. Hembrooke, F. Radlinski, and G. Gay. Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search. ACM Transactions on Information Systems (TOIS), 25 (2), 2007.
-
(2007)
ACM Transactions on Information Systems (TOIS)
, vol.25
, pp. 2
-
-
Joachims, T.1
Granka, L.2
Pan, B.3
Hembrooke, H.4
Radlinski, F.5
Gay, G.6
-
21
-
-
84863379285
-
Global ranking using continuous conditional random fields
-
T. Qin, T.-Y. Liu, X.-D. Zhang, D.-S. Wang, and H. Li. Global ranking using continuous conditional random fields. In NIPS, pages 1281-1288, 2008.
-
(2008)
NIPS
, pp. 1281-1288
-
-
Qin, T.1
Liu, T.-Y.2
Zhang, X.-D.3
Wang, D.-S.4
Li, H.5
-
22
-
-
57349173530
-
Learning to rank relational objects and its application to web search
-
T. Qin, T.-Y. Liu, X.-D. Zhang, D.-S. Wang, W.-Y. Xiong, and H. Li. Learning to rank relational objects and its application to web search. In WWW '08, pages 407-416, 2008.
-
(2008)
WWW '08
, pp. 407-416
-
-
Qin, T.1
Liu, T.-Y.2
Zhang, X.-D.3
Wang, D.-S.4
Xiong, W.-Y.5
Li, H.6
-
23
-
-
42549161120
-
Softrank: Optimizing non-smooth rank metrics
-
New York, NY, USA, ACM
-
M. Taylor, J. Guiver, S. Robertson, and T. Minka. Softrank: optimizing non-smooth rank metrics. In WSDM '08: Proceedings of the international conference on Web search and web data mining, pages 77-86, New York, NY, USA, 2008. ACM.
-
(2008)
WSDM '08: Proceedings of the International Conference on Web Search and Web Data Mining
, pp. 77-86
-
-
Taylor, M.1
Guiver, J.2
Robertson, S.3
Minka, T.4
-
24
-
-
71149095619
-
Boltzrank: Learning to maximize expected ranking gain
-
New York, NY, USA, ACM
-
M. N. Volkovs and R. S. Zemel. Boltzrank: learning to maximize expected ranking gain. In ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, pages 1089-1096, New York, NY, USA, 2009. ACM.
-
(2009)
ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning
, pp. 1089-1096
-
-
Volkovs, M.N.1
Zemel, R.S.2
-
25
-
-
36448954244
-
Adarank: A boosting algorithm for information retrieval
-
New York, NY, USA, ACM
-
J. Xu and H. Li. Adarank: a boosting algorithm for information retrieval. In SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, pages 391-398, New York, NY, USA, 2007. ACM.
-
(2007)
SIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
, pp. 391-398
-
-
Xu, J.1
Li, H.2
-
27
-
-
85161963897
-
A general boosting method and its application to learning ranking functions for web search
-
MIT Press
-
Z. Zheng, H. Zha, T. Zhang, O. Chapelle, K. Chen, and G. Sun. A general boosting method and its application to learning ranking functions for web search. In Advances in Neural Information Processing Systems 20, pages 1697-1704. MIT Press, 2008.
-
(2008)
Advances in Neural Information Processing Systems
, vol.20
, pp. 1697-1704
-
-
Zheng, Z.1
Zha, H.2
Zhang, T.3
Chapelle, O.4
Chen, K.5
Sun, G.6
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