Information Technology Reference
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15. Donmez, P., Svore, K.M., Burges, C.J.C.: On the local optimality of lambdarank. In: Proceed-
ings of the 32nd Annual International ACM SIGIR Conference on Research and Development
in Information Retrieval (SIGIR 2009), pp. 460-467 (2009)
16. Dwork, C., Kumar, R., Naor, M., Sivakumar, D.: Rank aggregation methods for the web.
In: Proceedings of the 10th International Conference on World Wide Web (WWW 2001),
pp. 613-622. ACM, New York (2001)
17. Fagin, R., Kumar, R., Sivakumar, D.: Efficient similarity search and classification via
rank aggregation. In: Proceedings of the 2003 ACM SIGMOD International Confer-
ence on Management of Data (SIGMOD 2003), pp. 301-312. ACM, New York (2003).
http://doi.acm.org/10.1145/872757.872795
18. Freund, Y., Iyer, R., Schapire, R., Singer, Y.: An efficient boosting algorithm for combining
preferences. Journal of Machine Learning Research 4 , 933-969 (2003)
19. Freund, Y., Schapire, R.E.: A decision-theoretic generalization of online learning and an ap-
plication to boosting. Journal of Computer and System Sciences 55 (1), 119-139 (1995)
20. Friedman, J.: Greedy function approximation: a gradient boosting machine. Annual Statistics
29 , 1189-1232 (2001)
21. Gao, J., Qi, H., Xia, X., Nie, J.: Linear discriminant model for information retrieval. In: Pro-
ceedings of the 28th Annual International ACM SIGIR Conference on Research and Devel-
opment in Information Retrieval (SIGIR 2005), pp. 290-297 (2005)
22. Herbrich, R., Obermayer, K., Graepel, T.: Large margin rank boundaries for ordinal regres-
sion. In: Advances in Large Margin Classifiers, pp. 115-132 (2000)
23. Joachims, T.: Optimizing search engines using clickthrough data. In: Proceedings of the 8th
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD
2002), pp. 133-142 (2002)
24. Joachims, T.: Training linear svms in linear time. In: Proceedings of the 12th ACM SIGKDD
International Conference on Knowledge Discovery and Data Mining (KDD 2006), pp. 217-
226 (2006)
25. Matveeva, I., Burges, C., Burkard, T., Laucius, A., Wong, L.: High accuracy retrieval with
multiple nested ranker. In: Proceedings of the 29th Annual International ACM SIGIR Con-
ference on Research and Development in Information Retrieval (SIGIR 2006), pp. 437-444
(2006)
26. Qin, T., Liu, T.-Y., Lai, W., Zhang, X.-D., Wang, D.-S., Li, H.: Ranking with multiple hyper-
planes. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research
and Development in Information Retrieval (SIGIR 2007), pp. 279-286 (2007)
27. Qin, T., Zhang, X.-D., Tsai, M.-F., Wang, D.-S., Liu, T.-Y., Li, H.: Query-level loss functions
for information retrieval. Information Processing and Management 44 (2), 838-855 (2008)
28. Rigutini, L., Papini, T., Maggini, M., Scarselli, F.: Learning to rank by a neural-based sorting
algorithm. In: SIGIR 2008 Workshop on Learning to Rank for Information Retrieval (LR4IR
2008) (2008)
29. Rudin, C.: Ranking with a p-norm push. In: Proceedings of the 19th Annual Conference on
Learning Theory (COLT 2006), pp. 589-604 (2006)
30. Shen, L., Joshi, A.K.: Ranking and reranking with perceptron. Journal of Machine Learning
60 (1-3), 73-96 (2005)
31. Sun, Z., Qin, T., Tao, Q., Wang, J.: Robust sparse rank learning for non-smooth ranking mea-
sures. In: Proceedings of the 32nd Annual International ACM SIGIR Conference on Research
and Development in Information Retrieval (SIGIR 2009), pp. 259-266 (2009)
32. Thurstone, L.: A law of comparative judgement. Psychological Review 34 , 34 (1927)
33. Tsai, M.-F., Liu, T.-Y., Qin, T., Chen, H.-H., Ma, W.-Y.: Frank: a ranking method with fidelity
loss. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research
and Development in Information Retrieval (SIGIR 2007), pp. 383-390 (2007)
34. Usunier, N., Buffoni, D., Gallinari, P.: Ranking with ordered weighted pairwise classification.
In: Proceedings of the 26th International Conference on Machine Learning (ICML 2009),
pp. 1057-1064 (2009)
35. Yager, R.R.: On ordered weighted averaging aggregation operators in multi-criteria decision
making. IEEE Transactions on Systems, Man, and Cybernetics 18 (1), 183-190 (1988)
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