{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:22:24Z","timestamp":1775744544781,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2007,7,23]],"date-time":"2007-07-23T00:00:00Z","timestamp":1185148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2007,7,23]]},"DOI":"10.1145\/1277741.1277790","type":"proceedings-article","created":{"date-parts":[[2008,9,18]],"date-time":"2008-09-18T11:59:52Z","timestamp":1221739192000},"page":"271-278","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":421,"title":["A support vector method for optimizing average precision"],"prefix":"10.1145","author":[{"given":"Yisong","family":"Yue","sequence":"first","affiliation":[{"name":"Cornell University"}]},{"given":"Thomas","family":"Finley","sequence":"additional","affiliation":[{"name":"Cornell University"}]},{"given":"Filip","family":"Radlinski","sequence":"additional","affiliation":[{"name":"Cornell University"}]},{"given":"Thorsten","family":"Joachims","sequence":"additional","affiliation":[{"name":"Cornell University"}]}],"member":"320","published-online":{"date-parts":[[2007,7,23]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/188490.188554"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the International Conference on Advances in Neural Information Processing Systems (NIPS)","author":"Burges C. J. C.","year":"2006","unstructured":"C. J. C. Burges , R. Ragno , and Q. Le . Learning to rank with non-smooth cost functions . In Proceedings of the International Conference on Advances in Neural Information Processing Systems (NIPS) , 2006 . C. J. C. Burges, R. Ragno, and Q. Le. Learning to rank with non-smooth cost functions. In Proceedings of the International Conference on Advances in Neural Information Processing Systems (NIPS), 2006."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148205"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148289"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015432"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143874"},{"key":"e_1_3_2_1_8_1","volume-title":"Overview of the TREC-9 web track","author":"Hawking D.","year":"2000","unstructured":"D. Hawking . Overview of the TREC-9 web track . 2000 . D. Hawking. Overview of the TREC-9 web track. 2000."},{"key":"e_1_3_2_1_9_1","volume-title":"Overview of the TREC-2001 web track","author":"Hawking D.","year":"2001","unstructured":"D. Hawking and N. Craswell . Overview of the TREC-2001 web track . Nov. 2001 . D. Hawking and N. Craswell. Overview of the TREC-2001 web track. Nov. 2001."},{"key":"e_1_3_2_1_10_1","volume-title":"Large margin rank boundaries for ordinal regression. Advances in large margin classifiers","author":"Herbrich R.","year":"2000","unstructured":"R. Herbrich , T. Graepel , and K. Obermayer . Large margin rank boundaries for ordinal regression. Advances in large margin classifiers , 2000 . R. Herbrich, T. Graepel, and K. Obermayer. Large margin rank boundaries for ordinal regression. Advances in large margin classifiers, 2000."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015366"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/345508.345545"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102399"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/383952.383970"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012406528296"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1076034.1076115"},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Morik K.","year":"1999","unstructured":"K. Morik , P. Brockhausen , and T. Joachims . Combining statistical learning with a knowledge-based approach . In Proceedings of the International Conference on Machine Learning , 1999 . K. Morik, P. Brockhausen, and T. Joachims. Combining statistical learning with a knowledge-based approach. In Proceedings of the International Conference on Machine Learning, 1999."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1108\/eb026647"},{"key":"e_1_3_2_1_19_1","first-page":"1453","volume-title":"Journal of Machine Learning Research (JMLR)","author":"Tsochantaridis I.","year":"2005","unstructured":"I. Tsochantaridis , T. Hofmann , T. Joachims , and Y. Altun . Large margin methods for structured and interdependent output variables . Journal of Machine Learning Research (JMLR) , pages 1453 -- 1484 , 2005 . I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun. Large margin methods for structured and interdependent output variables. Journal of Machine Learning Research (JMLR), pages 1453--1484, 2005."},{"key":"e_1_3_2_1_20_1","volume-title":"Statistical Learning Theory","author":"Vapnik V.","year":"1998","unstructured":"V. Vapnik . Statistical Learning Theory . Wiley and Sons Inc ., 1998 . V. Vapnik. Statistical Learning Theory. Wiley and Sons Inc., 1998."},{"key":"e_1_3_2_1_21_1","volume-title":"Proceedings of the International Conference on Machine Learning (ICML)","author":"Yan L.","year":"2003","unstructured":"L. Yan , R. Dodier , M. Mozer , and R. Wolniewicz . Optimizing classifier performance via approximation to the Wilcoxon-Mann-Witney statistic . In Proceedings of the International Conference on Machine Learning (ICML) , 2003 . L. Yan, R. Dodier, M. Mozer, and R. Wolniewicz. Optimizing classifier performance via approximation to the Wilcoxon-Mann-Witney statistic. In Proceedings of the International Conference on Machine Learning (ICML), 2003."}],"event":{"name":"SIGIR07: The 30th Annual International SIGIR Conference","location":"Amsterdam The Netherlands","acronym":"SIGIR07","sponsor":["ACM Association for Computing Machinery","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1277741.1277790","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1277741.1277790","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T14:58:14Z","timestamp":1750258694000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1277741.1277790"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,7,23]]},"references-count":21,"alternative-id":["10.1145\/1277741.1277790","10.1145\/1277741"],"URL":"https:\/\/doi.org\/10.1145\/1277741.1277790","relation":{},"subject":[],"published":{"date-parts":[[2007,7,23]]},"assertion":[{"value":"2007-07-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}