{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T12:10:30Z","timestamp":1772021430720,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2008,7,20]],"date-time":"2008-07-20T00:00:00Z","timestamp":1216512000000},"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":[[2008,7,20]]},"DOI":"10.1145\/1390334.1390379","type":"proceedings-article","created":{"date-parts":[[2008,7,22]],"date-time":"2008-07-22T13:46:39Z","timestamp":1216734399000},"page":"251-258","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":50,"title":["Learning to rank with partially-labeled data"],"prefix":"10.1145","author":[{"given":"Kevin","family":"Duh","sequence":"first","affiliation":[{"name":"University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katrin","family":"Kirchhoff","sequence":"additional","affiliation":[{"name":"University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2008,7,20]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143848"},{"key":"e_1_3_2_1_2_1","volume":"6","author":"Ando R. K.","year":"2005","unstructured":"R. K. Ando and T. Zhang . A framework for learning predictive structures from multiple tasks and unlabeled data. In Journal of Machine Learning Research , volume 6 , 2005 . R. K. Ando and T. Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data. In Journal of Machine Learning Research, volume 6, 2005.","journal-title":"In Journal of Machine Learning Research"},{"key":"e_1_3_2_1_3_1","volume-title":"Neural Information Processing Systems","author":"Ben-David S.","year":"2006","unstructured":"S. Ben-David , J. Blitzer , K. Crammer , and F. Pereira . Analysis of representations for domain adaptation . In Neural Information Processing Systems , 2006 . S. Ben-David, J. Blitzer, K. Crammer, and F. Pereira. Analysis of representations for domain adaptation. In Neural Information Processing Systems, 2006."},{"key":"e_1_3_2_1_4_1","volume-title":"NIPS","author":"Burges C.","year":"2006","unstructured":"C. Burges , R. Ragno , and Q. Le . Learning to rank with nonsmooth cost functions . In NIPS , 2006 . C. Burges, R. Ragno, and Q. Le. Learning to rank with nonsmooth cost functions. In NIPS, 2006."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"e_1_3_2_1_6_1","volume-title":"NIPS Wksp on Learning to Rank","author":"Chu W.","year":"2005","unstructured":"W. Chu and Z. Ghahramani . Extensions of gaussian processes for ranking: semi-supervised and active learning . In NIPS Wksp on Learning to Rank , 2005 . W. Chu and Z. Ghahramani. Extensions of gaussian processes for ranking: semi-supervised and active learning. In NIPS Wksp on Learning to Rank, 2005."},{"key":"e_1_3_2_1_7_1","volume-title":"Neural Information Processing Systems (NIPS)","author":"Crammer K.","year":"2001","unstructured":"K. Crammer and Y. Singer . Pranking with ranking . In Neural Information Processing Systems (NIPS) , 2001 . K. Crammer and Y. Singer. Pranking with ranking. In Neural Information Processing Systems (NIPS), 2001."},{"key":"e_1_3_2_1_8_1","first-page":"4","author":"Freund Y.","year":"2003","unstructured":"Y. Freund , R. Iyer , R. Schapire , and Y. Singer . An efficient boosting algorithm for combining preferences. Journal of Machine Learning Research , 4 , 2003 . Y. Freund, R. Iyer, R. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. Journal of Machine Learning Research, 4, 2003.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277811"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1027527.1027531"},{"key":"e_1_3_2_1_11_1","volume-title":"Advances in Large Margin Classifiers","author":"Herbrich R.","year":"2000","unstructured":"R. Herbrich , T. Graepel , and K. Obermayer . Advances in Large Margin Classifiers , chapter Large margin rank boundaries for ordinal regression. MIT Press , 2000 . R. Herbrich, T. Graepel, and K. Obermayer. Advances in Large Margin Classifiers, chapter Large margin rank boundaries for ordinal regression. MIT Press, 2000."},{"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\/775047.775067"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/324133.324140"},{"key":"e_1_3_2_1_15_1","volume-title":"ICML","author":"Kondor I.","year":"2002","unstructured":"I. Kondor and J. Lafferty . Diffusion kernels on graphs and other discrete structures . In ICML , 2002 . I. Kondor and J. Lafferty. Diffusion kernels on graphs and other discrete structures. In ICML, 2002."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/258525.258587"},{"key":"e_1_3_2_1_17_1","volume-title":"NIPS","author":"Li P.","year":"2007","unstructured":"P. Li , C. Burges , and Q. Wu . McRank: Learning to rank using classification and gradient boosting . In NIPS , 2007 . P. Li, C. Burges, and Q. Wu. McRank: Learning to rank using classification and gradient boosting. In NIPS, 2007."},{"key":"e_1_3_2_1_18_1","volume-title":"SIGIR Workshop on Learning to Rank for IR (LR4IR)","author":"Liu T.-Y.","year":"2007","unstructured":"T.-Y. Liu , T. Qin , J. Xu , W. Xiong , and H. Li . LETOR: Benchmark dataset for research on learning to rank for information retrieval . In SIGIR Workshop on Learning to Rank for IR (LR4IR) , 2007 . T.-Y. Liu, T. Qin, J. Xu, W. Xiong, and H. Li. LETOR: Benchmark dataset for research on learning to rank for information retrieval. In SIGIR Workshop on Learning to Rank for IR (LR4IR), 2007."},{"key":"e_1_3_2_1_19_1","volume-title":"NIPS","author":"Mason L.","year":"2000","unstructured":"L. Mason , J. Baxter , P. Bartless , and M. Frean . Boosting as gradient descent . In NIPS , 2000 . L. Mason, J. Baxter, P. Bartless, and M. Frean. Boosting as gradient descent. In NIPS, 2000."},{"key":"e_1_3_2_1_20_1","volume-title":"Direct maximization of rank-based metrics. Technical report","author":"Metzler D.","year":"2005","unstructured":"D. Metzler . Direct maximization of rank-based metrics. Technical report , University of Massachusetts , Amherst CIIR, 2005 . D. Metzler. Direct maximization of rank-based metrics. Technical report, University of Massachusetts, Amherst CIIR, 2005."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273592"},{"issue":"1","key":"e_1_3_2_1_22_1","volume":"53","author":"Robertson S.","year":"1997","unstructured":"S. Robertson . Overview of the Okapi projects. Journal of Documentation , 53 ( 1 ), 1997 . S. Robertson. Overview of the Okapi projects. Journal of Documentation, 53(1), 1997.","journal-title":"Journal of Documentation"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007614523901"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017467"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.5555\/975545"},{"key":"e_1_3_2_1_27_1","volume-title":"Int'l Conf. on Multidisciplinary Info Sci\/Tech","author":"Truong T.","year":"2006","unstructured":"T. Truong , M.-R. Amini , and P. Gallinari . Learning to rank with partially labeled training data . In Int'l Conf. on Multidisciplinary Info Sci\/Tech , 2006 . T. Truong, M.-R. Amini, and P. Gallinari. Learning to rank with partially labeled training data. In Int'l Conf. on Multidisciplinary Info Sci\/Tech, 2006."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277808"},{"key":"e_1_3_2_1_29_1","volume-title":"Microsoft Research Asia","author":"Wang J.","year":"2005","unstructured":"J. Wang , M. Li , Z. Li , and W.-Y. Ma . Learning ranking function via relevance propagation. Technical report , Microsoft Research Asia , 2005 . J. Wang, M. Li, Z. Li, and W.-Y. Ma. Learning ranking function via relevance propagation. Technical report, Microsoft Research Asia, 2005."},{"key":"e_1_3_2_1_30_1","volume-title":"Protein ranking by semi-supervised network propagation. BMC Bioinformatics, 7","author":"Weston J.","year":"2006","unstructured":"J. Weston , R. Kuang , C. Leslie , and W. S. Noble . Protein ranking by semi-supervised network propagation. BMC Bioinformatics, 7 , 2006 . J. Weston, R. Kuang, C. Leslie, and W. S. Noble. Protein ranking by semi-supervised network propagation. BMC Bioinformatics, 7, 2006."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/243199.243202"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277809"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277790"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/383952.384019"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277792"},{"key":"e_1_3_2_1_36_1","volume-title":"NIPS","author":"Zhou D.","year":"2004","unstructured":"D. Zhou , J. Weston , A. Gretton , O. Bousquet , and B. Sch\u00f6kopf . Ranking on data manifolds . In NIPS , 2004 . D. Zhou, J. Weston, A. Gretton, O. Bousquet, and B. Sch\u00f6kopf. Ranking on data manifolds. In NIPS, 2004."},{"key":"e_1_3_2_1_37_1","volume-title":"Technical Report 1530","author":"Zhu X.","year":"2005","unstructured":"X. Zhu . Semi-supervised learning literature survey. Technical Report 1530 , University of Wisconsin, Madison, Computer Science Dept ., 2005 . X. Zhu. Semi-supervised learning literature survey. Technical Report 1530, University of Wisconsin, Madison, Computer Science Dept., 2005."}],"event":{"name":"SIGIR '08: The 31st Annual International ACM SIGIR Conference","location":"Singapore Singapore","acronym":"SIGIR '08","sponsor":["ACM Association for Computing Machinery","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1390334.1390379","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1390334.1390379","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T14:47:20Z","timestamp":1750258040000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1390334.1390379"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,7,20]]},"references-count":36,"alternative-id":["10.1145\/1390334.1390379","10.1145\/1390334"],"URL":"https:\/\/doi.org\/10.1145\/1390334.1390379","relation":{},"subject":[],"published":{"date-parts":[[2008,7,20]]},"assertion":[{"value":"2008-07-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}