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Volumn , Issue , 2010, Pages 192-199

Ranking entity facets based on user click feedback

Author keywords

[No Author keywords available]

Indexed keywords

BOOSTED DECISION TREES; CLICK-THROUGH RATE; CUMULATED GAIN; EMPIRICAL EVALUATIONS; FACETED SEARCH; FEEDBACK MODEL; LINEAR COMBINATIONS; RETRIEVAL PERFORMANCE; TEST SETS;

EID: 79952075988     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSC.2010.33     Document Type: Conference Paper
Times cited : (9)

References (18)
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    • Friedman, J.H.1
  • 10
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  • 13
    • 36448953520 scopus 로고    scopus 로고
    • A regression framework for learning ranking functions using relative relevance judgments
    • New York, NY, USA: ACM
    • Z. Zheng, K. Chen, G. Sun, and H. Zha, "A regression framework for learning ranking functions using relative relevance judgments," in SIGIR '07. New York, NY, USA: ACM, 2007, pp. 287-294.
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    • Zheng, Z.1    Chen, K.2    Sun, G.3    Zha, H.4
  • 14
    • 0037186544 scopus 로고    scopus 로고
    • Stochastic gradient boosting
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    • (1999) Advances in Kernel Methods: Support Vector Learning , pp. 169-184
    • Joachims, T.1
  • 16
    • 64149115569 scopus 로고    scopus 로고
    • Sparse online learning via truncated gradient
    • J. Langford, L. Li, and T. Zhang, "Sparse online learning via truncated gradient," J. Mach. Learn. Res., vol. 10, pp. 777-801, 2009.
    • (2009) J. Mach. Learn. Res. , vol.10 , pp. 777-801
    • Langford, J.1    Li, L.2    Zhang, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.