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Volumn 2002-July, Issue , 2002, Pages 489-496

Ranking algorithms for named-entity extraction: Boosting and the voted perceptron

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; MAXIMUM ENTROPY METHODS;

EID: 85045072379     PISSN: 0736587X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (179)

References (18)
  • 1
    • 0000431299 scopus 로고    scopus 로고
    • Stochastic Attribute-Value Grammars
    • Abney, S. 1997. Stochastic Attribute-Value Grammars. Computational Linguistics, 23(4):597-618.
    • (1997) Computational Linguistics , vol.23 , Issue.4 , pp. 597-618
    • Abney, S.1
  • 6
    • 1942419006 scopus 로고    scopus 로고
    • Convolution Kernels for Natural Language
    • Collins, M., and Duffy, N. (2001). Convolution Kernels for Natural Language. In Proceedings of NIPS 14.
    • (2001) Proceedings of NIPS , vol.14
    • Collins, M.1    Duffy, N.2
  • 7
    • 33646057547 scopus 로고    scopus 로고
    • New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron
    • Collins, M., and Duffy, N. (2002). New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron. In Proceedings of ACL 2002.
    • (2002) Proceedings of ACL 2002
    • Collins, M.1    Duffy, N.2
  • 8
    • 85127836544 scopus 로고    scopus 로고
    • Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with the Perceptron Algorithm
    • Collins, M. (2002). Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with the Perceptron Algorithm. In Proceedings of EMNLP 2002.
    • (2002) Proceedings of EMNLP 2002
    • Collins, M.1
  • 11
    • 0033281425 scopus 로고    scopus 로고
    • Large Margin Classification using the Perceptron Algorithm
    • Freund, Y. & Schapire, R. (1999). Large Margin Classification using the Perceptron Algorithm. In Machine Learning, 37(3):277-296.
    • (1999) Machine Learning , vol.37 , Issue.3 , pp. 277-296
    • Freund, Y.1    Schapire, R.2
  • 14
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • Lafferty, J., McCallum, A., and Pereira, F. (2001). Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of ICML 2001.
    • (2001) Proceedings of ICML 2001
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 15
    • 0000747663 scopus 로고    scopus 로고
    • Maximum entropy markov models for information extraction and segmentation
    • McCallum, A., Freitag, D., and Pereira, F. (2000) Maximum entropy markov models for information extraction and segmentation. In Proceedings of ICML 2000.
    • (2000) Proceedings of ICML 2000
    • McCallum, A.1    Freitag, D.2    Pereira, F.3
  • 17
    • 11144273669 scopus 로고
    • The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain
    • (Reprinted in Neurocomputing (MIT Press, 1998))
    • Rosenblatt, F. (1958). The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain. Psychological Review, 65, 386-408. (Reprinted in Neurocomputing (MIT Press, 1998).)
    • (1958) Psychological Review , vol.65 , pp. 386-408
    • Rosenblatt, F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.