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Volumn , Issue , 2007, Pages 361-369

Query expansion using probabilistic local feedback with application to multimedia retrieval

Author keywords

Multimedia retrieval; Probabilistic local feedback; Query expansion

Indexed keywords

BASELINE METHODS; ITERATIVE PROCESS; LOCAL ANALYSIS; MULTIMEDIA RETRIEVAL; PROBABILISTIC INTERPRETATIONS; PROBABILISTIC LOCAL FEEDBACK; PROBABILISTIC RETRIEVALS; QUERY EXPANSION; QUERY TERMS; RETRIEVAL ACCURACIES; RETRIEVAL MODELS; SIMPLE OPERATIONS; TEXT RETRIEVALS; TRECVID;

EID: 57349164677     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1321440.1321492     Document Type: Conference Paper
Times cited : (16)

References (23)
  • 2
    • 50049112634 scopus 로고
    • Using probabilistic models of document retrieval without relevance information
    • W. B. Croft and D. J. Harper. Using probabilistic models of document retrieval without relevance information. Document retrieval systems, pages 161-171, 1988.
    • (1988) Document retrieval systems , pp. 161-171
    • Croft, W.B.1    Harper, D.J.2
  • 5
    • 77957175435 scopus 로고
    • Probabilistic models in information retrieval
    • N. Fuhr. Probabilistic models in information retrieval. The Computer Journal, 35(3):243-255, 1992.
    • (1992) The Computer Journal , vol.35 , Issue.3 , pp. 243-255
    • Fuhr, N.1
  • 8
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • Morgan Kaufmann, San Francisco, CA
    • J. Lafferty, A. McCallum, and F. Pereira. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proc. 18th Intl. Conf. on Machine Learning, pages 282-289. Morgan Kaufmann, San Francisco, CA, 2001.
    • (2001) Proc. 18th Intl. Conf. on Machine Learning , pp. 282-289
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 12
    • 0001406440 scopus 로고
    • A mean field theory learning algorithm for neural networks
    • C. Peterson and J. Anderson. A mean field theory learning algorithm for neural networks. Complex Systems, 1:995-1019, 1987.
    • (1987) Complex Systems , vol.1 , pp. 995-1019
    • Peterson, C.1    Anderson, J.2
  • 17
    • 33750321745 scopus 로고    scopus 로고
    • Regularized estimation of mixture models for robust pseudo-relevance feedback
    • New York, NY, USA, ACM Press
    • T. Tao and C. Zhai. Regularized estimation of mixture models for robust pseudo-relevance feedback. In Proceedings of the 29th annual international ACM SIGIR conference, pages 162-169, New York, NY, USA, 2006. ACM Press.
    • (2006) Proceedings of the 29th annual international ACM SIGIR conference , pp. 162-169
    • Tao, T.1    Zhai, C.2
  • 20
    • 0003029479 scopus 로고    scopus 로고
    • Improving the effectiveness of information retrieval with local context analysis
    • J. Xu and W. B. Croft. Improving the effectiveness of information retrieval with local context analysis. ACM Transaction Information System, 18(1):79-112, 2000.
    • (2000) ACM Transaction Information System , vol.18 , Issue.1 , pp. 79-112
    • Xu, J.1    Croft, W.B.2
  • 23
    • 63449083921 scopus 로고    scopus 로고
    • Y. Yang and J. O. Pedersen. A comparative study on feature selection in text categorization. In Proc. of the 14th ICML, pages 412-420, 1997.
    • Y. Yang and J. O. Pedersen. A comparative study on feature selection in text categorization. In Proc. of the 14th ICML, pages 412-420, 1997.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.