Deep versus shallow judgments in learning to rank

Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009

Volumn , Issue , 2009, Pages 662-663

  Yilmaz, Emine ^a   Robertson, Stephen ^a  

^a MICROSOFT RESEARCH   (United Kingdom)

Author keywords

Learning to rank; Relevance judgments; Training

Indexed keywords

COST EFFECTIVE; LEARNING METHODS; LEARNING TO RANK; RELEVANCE JUDGMENT; TRAINING DATA; TRAINING SETS;

EDUCATION; INFORMATION RETRIEVAL; INFORMATION SERVICES;

RESEARCH;

EID: 72449142196     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1571941.1572066     Document Type: Conference Paper

References (4)

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2. C. J. C. Burges, R. Ragno, and Q. V. Le. Learning to rank with nonsmooth cost functions. In B. Schölkopf, J. C. Platt, and T. Hoffman, editors, NIPS, pages 193{200. MIT Press, 2006.
3. B. Carterette, V. Pavlu, E. Kanoulas, J. A. Aslam, and J. Allan. Evaluation over thousands of queries. In SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pages 651-658, New York, NY, USA, 2008. ACM.
4. K. Järvelin and J. Kekäläinen. IR evaluation methods for retrieving highly relevant documents. In SIGIR '00: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, pages 41-48, New York, NY, USA, 2000. ACM.