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Volumn , Issue , 2009, Pages 315-323

Ranking measures and loss functions in learning to rank

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); INFORMATION RETRIEVAL; LEARNING SYSTEMS;

EID: 84863035221     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (221)

References (19)
  • 5
    • 55349114379 scopus 로고    scopus 로고
    • Statistical analysis of bayes optimal subset ranking
    • D. Cossock and T. Zhang. Statistical analysis of bayes optimal subset ranking. Information Theory, 54:5140-5154, 2008.
    • (2008) Information Theory , vol.54 , pp. 5140-5154
    • Cossock, D.1    Zhang, T.2
  • 10
    • 85162006799 scopus 로고    scopus 로고
    • Mcrank: Learning to rank using multiple classification and gradient boosting
    • Cambridge, MA MIT
    • P. Li, C. Burges, and Q. Wu. Mcrank: Learning to rank using multiple classification and gradient boosting. In NIPS '07: Advances in Neural Information Processing Systems 20, pages 897-904, Cambridge, MA, 2008. MIT.
    • (2008) NIPS '07: Advances in Neural Information Processing Systems , vol.20 , pp. 897-904
    • Li, P.1    Burges, C.2    Wu, Q.3
  • 11
    • 45449095122 scopus 로고    scopus 로고
    • Letor: Benchmark dataset for research on learning to rank for information retrieval
    • San Francisco Morgan Kaufmann
    • T.-Y. Liu, J. Xu, T. Qin, W.-Y. Xiong, and H. Li. Letor: Benchmark dataset for research on learning to rank for information retrieval. In SIGIR '07 Workshop, San Francisco, 2007. Morgan Kaufmann.
    • (2007) SIGIR '07 Workshop
    • Liu, T.-Y.1    Xu, J.2    Qin, T.3    Xiong, W.-Y.4    Li, H.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.