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Volumn , Issue , 2001, Pages

Feature space restructuring for SVMs with application to text categorization

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS; SUPPORT VECTOR MACHINES;

EID: 85126970015     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (21)
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    • An Information Maximization Approach to Blind Separation and Blind Deconvolution
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    • Bell, A. J.1    Sejnowski, T. J.2
  • 4
    • 0030832881 scopus 로고    scopus 로고
    • The 'Independent Components' of Natural Scenes are Edge Filters
    • Bell, A. J. and Sejnowski, T. J. 1997. The 'Independent Components' of Natural Scenes are Edge Filters. Vision Research, 37(23), pp. 3327-3338.
    • (1997) Vision Research , vol.37 , Issue.23 , pp. 3327-3338
    • Bell, A. J.1    Sejnowski, T. J.2
  • 6
    • 85119351504 scopus 로고    scopus 로고
    • Semi-Supervised Support Vector Machines for Unlabeled Data Classification
    • Glenn, F. and Mangasarian, O. 2001. Semi-Supervised Support Vector Machines for Unlabeled Data Classification. Optimization Methods and Software, pp. 1-14.
    • (2001) Optimization Methods and Software , pp. 1-14
    • Glenn, F.1    Mangasarian, O.2
  • 8
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    • Restructuring Sparse High Dimensional Data for Effective Retrieval
    • and Viola. P
    • Isbell, C. and Viola. P. 1998. Restructuring Sparse High Dimensional Data for Effective Retrieval. Advances in Neural Information Processing Systems, volume 11.
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    • Isbell, C.1
  • 9
    • 84957069814 scopus 로고    scopus 로고
    • Text Categorization with Support Vector Machines: Learning with Many Relevant Features
    • Joachims, T. 1998. Text Categorization with Support Vector Machines: Learning with Many Relevant Features. Proceedings of the European Conference on Machine Learning, pp. 137-142.
    • (1998) Proceedings of the European Conference on Machine Learning , pp. 137-142
    • Joachims, T.1
  • 10
    • 0001938951 scopus 로고    scopus 로고
    • Transductive Inference for Text Classification using Support Vector Machines
    • Joachims, T. 1999a. Transductive Inference for Text Classification using Support Vector Machines. Machine Learning - Proc. 16th Int'l Conf. (ICML '99), pp. 200-209.
    • (1999) Machine Learning - Proc. 16th Int'l Conf. (ICML '99) , pp. 200-209
    • Joachims, T.1
  • 15
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    • Text Classification from Labeled and Unlabeled Documents using EM
    • (/3)
    • Nigam, K., McCallum, A., Thrun, S. and Mitchell, T. 2000. Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning, 39(2/3). pp. 103-134.
    • (2000) Machine Learning , vol.39 , Issue.2 , pp. 103-134
    • Nigam, K.1    McCallum, A.2    Thrun, S.3    Mitchell, T.4
  • 21
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    • An Evaluation of Statistical Approaches to Text Categorization
    • Yang, Y. An Evaluation of Statistical Approaches to Text Categorization. Information Retrieval, volume 1, 1-2, pp. 69-90.
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    • Yang, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.