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Volumn 19, Issue 1-2, 2004, Pages 131-147

Iterative cross-training: An algorithm for learning from unlabeled web pages

Author keywords

[No Author keywords available]

Indexed keywords

HTML; LEARNING ALGORITHMS; NEURAL NETWORKS; SEARCH ENGINES; TEXT PROCESSING; WEBSITES; WORD PROCESSING;

EID: 1142279557     PISSN: 08848173     EISSN: None     Source Type: Journal    
DOI: 10.1002/int.10157     Document Type: Article
Times cited : (7)

References (19)
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    • Apte, C.1    Damerau, F.2
  • 3
    • 0001345686 scopus 로고    scopus 로고
    • Context-sensitive learning methods for text categorization
    • Cohen WW, Singer Y. Context-sensitive learning methods for text categorization. ACM Trans Infn Syst 1998; 17(2):141-173.
    • (1998) ACM Trans Infn Syst , vol.17 , Issue.2 , pp. 141-173
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    • A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization
    • Morgan Kaufmann
    • Joachims J. A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization. In: Proc of the 14th Int Conf on Machine Learning. San Francisco, CA: Morgan Kaufmann; 1997. pp 143-151.
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    • Joachims, J.1
  • 5
    • 84957069814 scopus 로고    scopus 로고
    • Text categorization with support vector machines: Learning with many relevant features
    • New York: Springer Verlag
    • Joachims T. Text categorization with support vector machines: Learning with many relevant features. In: Proc of the 10th Eur Conf on Machine Learning. New York: Springer Verlag; 1998. pp 137-142.
    • (1998) Proc of the 10th Eur Conf on Machine Learning , pp. 137-142
    • Joachims, T.1
  • 7
    • 27144441097 scopus 로고    scopus 로고
    • An evaluation of statistical approaches to text categorizing
    • Yang Y. An evaluation of statistical approaches to text categorizing. Inf Retriev J 1999; 1:69-90.
    • (1999) Inf Retriev J , vol.1 , pp. 69-90
    • Yang, Y.1
  • 9
    • 0033886806 scopus 로고    scopus 로고
    • Text classification from labeled and unlabeled documents using EM
    • Nigam K, McCallum A, Thrun S, Mitchell T. Text classification from labeled and unlabeled documents using EM. Mach Learning 2000; 39:103-134.
    • (2000) Mach Learning , vol.39 , pp. 103-134
    • Nigam, K.1    McCallum, A.2    Thrun, S.3    Mitchell, T.4
  • 13
    • 0004255908 scopus 로고    scopus 로고
    • New York: McGraw-Hill
    • Mitchell T. Machine learning. New York: McGraw-Hill; 1997. pp 180-184.
    • (1997) Machine Learning , pp. 180-184
    • Mitchell, T.1
  • 15
    • 0003141937 scopus 로고    scopus 로고
    • Feature selection in statistical learning of text categorization
    • San Francisco, CA: Morgan Kaufmann
    • Yang Y, Pederson J. Feature selection in statistical learning of text categorization. In: Proc of the 14th Int Conf on Machine Learning. San Francisco, CA: Morgan Kaufmann; 1997. pp 412-420.
    • (1997) Proc of the 14th Int Conf on Machine Learning , pp. 412-420
    • Yang, Y.1    Pederson, J.2
  • 17
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    • An algorithm for suffix stripping
    • Porter MF. An algorithm for suffix stripping. Program. 1980; 14:130-137.
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  • 18
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    • Maximum likelihood from incomplete data via the EM algorithm
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    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.