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Volumn , Issue , 2009, Pages 1811-1814

A machine learning approach for improved BM25 retrieval

Author keywords

BM25; Learning to rank; Retrieval models; Web search

Indexed keywords

COMMON INFORMATION; DATA-DRIVEN APPROACH; LEARNING TO RANK; LINEAR FUNCTIONS; MACHINE-LEARNING; PARAMETER-TUNING; REAL-WORLD; RETRIEVAL EFFECTIVENESS; RETRIEVAL MODELS; WEB DATA; WEB SEARCHES;

EID: 74549202684     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1645953.1646237     Document Type: Conference Paper
Times cited : (54)

References (25)
  • 2
    • 74549122904 scopus 로고    scopus 로고
    • C. Burges, R. Ragno, and Q. Le. Learning to rank with nonsmooth cost functions. In Advances in Neural Information Processing Systems (NIPS), 2006. See also MSR Technical Report MSR-TR-2006-60.
    • C. Burges, R. Ragno, and Q. Le. Learning to rank with nonsmooth cost functions. In Advances in Neural Information Processing Systems (NIPS), 2006. See also MSR Technical Report MSR-TR-2006-60.
  • 9
    • 34547452270 scopus 로고    scopus 로고
    • On setting the hyper-parameters of term frequency normalization for information retrieval
    • B. He and I. Ounis. On setting the hyper-parameters of term frequency normalization for information retrieval. ACM Transactions on Information Systems (TOIS), 25(3):13, 2007.
    • (2007) ACM Transactions on Information Systems (TOIS) , vol.25 , Issue.3 , pp. 13
    • He, B.1    Ounis, I.2
  • 11
    • 0242456822 scopus 로고    scopus 로고
    • Optimizing search engines using clickthrough data
    • T. Joachims. Optimizing search engines using clickthrough data. In SIGKDD, pages 133-142, 2002.
    • (2002) SIGKDD , pp. 133-142
    • Joachims, T.1
  • 19
    • 0343169734 scopus 로고    scopus 로고
    • A probabilistic model of information retrieval: Development and comparative experiments
    • K. Sparck-Jones, S. Walker, and S. Robertson. A probabilistic model of information retrieval: development and comparative experiments. Information Processing and Management, 36:809-840, 2000.
    • (2000) Information Processing and Management , vol.36 , pp. 809-840
    • Sparck-Jones, K.1    Walker, S.2    Robertson, S.3
  • 20
    • 74549117620 scopus 로고    scopus 로고
    • A machine learning approach for improved bm25 retrieval
    • MSR-TR-2009-92
    • K. Svore and C. Burges. A machine learning approach for improved bm25 retrieval. Microsoft Technical Report MSR-TR-2009-92, 2009.
    • (2009) Microsoft Technical Report
    • Svore, K.1    Burges, C.2
  • 25
    • 72449175629 scopus 로고    scopus 로고
    • On using simultaneous perturbation stochastic approximation for IR measures, and the empirical optimality of LambdaRank
    • Y. Yue and C. Burges. On using simultaneous perturbation stochastic approximation for IR measures, and the empirical optimality of LambdaRank. NIPS Machine Learning for Web Search Workshop, 2007.
    • (2007) NIPS Machine Learning for Web Search Workshop
    • Yue, Y.1    Burges, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.