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Volumn , Issue , 2002, Pages 133-142

Optimizing search engines using clickthrough data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA RECORDING; INFORMATION RETRIEVAL SYSTEMS; MATHEMATICAL MODELS; METADATA; NEURAL NETWORKS; OPTIMIZATION;

EID: 0242456822     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/775047.775067     Document Type: Conference Paper
Times cited : (3401)

References (26)
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    • (2000) Advances in Large Margin Classifiers , pp. 115-132
    • Herbrich, R.1    Graepel, T.2    Obermayer, K.3
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    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • In B. Schölkopf, C. Burges, and A. Smola, editors; MIT Press, Cambridge, MA
    • T. Joachims. Making large-scale SVM learning practical. In B. Schölkopf, C. Burges, and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, chapter 11. MIT Press, Cambridge, MA, 1999.
    • (1999) Advances in Kernel Methods - Support Vector Learning, Chapter 11
    • Joachims, T.1
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    • T. Joachims. Unbiased evaluation of retrieval quality using clickthrough data. Technical report, Cornell University, Department of Computer Science, 2002. http://www:joachims.org.
    • (2002)
    • Joachims, T.1
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    • Salton, G.1    Buckley, C.2
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    • Analysis of a very large altavista query log
    • Technical Report SRC 1998-014, Digital Systems Research Center
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    • (1998)
    • Silverstein, C.1    Henzinger, M.2    Marais, H.3    Moricz, M.4
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    • Measuring retrieval effectiveness based on user preference of documents
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    • Yao, Y.1


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