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Volumn , Issue , 2009, Pages 280-287

Learning with annotation noise

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL LINGUISTICS;

EID: 84858430682     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1687878.1687919     Document Type: Conference Paper
Times cited : (105)

References (32)
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  • 2
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    • From annotator agreement to noise models
    • accepted for publication
    • Beata Beigman Klebanov and Eyal Beigman. 2009. From Annotator Agreement to Noise Models. Computational Linguistics, accepted for publication.
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    • Klebanov, B.B.1    Beigman, E.2
  • 5
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    • Carreras, X.1    Màrquez, L.2    Castro, J.3
  • 9
    • 33646057547 scopus 로고    scopus 로고
    • New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron
    • Philadelphia, USA
    • Michael Collins and Nigel Duffy. 2002. New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pages 263-370, Philadelphia, USA.
    • (2002) Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , pp. 263-370
    • Collins, M.1    Duffy, N.2
  • 11
    • 85127836544 scopus 로고    scopus 로고
    • Discriminative training methods for hidden Markov hodels: Theory and experiments with perceptron algorithms
    • Philadelphia, USA
    • Michael Collins. 2002a. Discriminative Training Methods for Hidden Markov Hodels: Theory and Experiments with Perceptron Algorithms. In Proceedings of the Empirical Methods in Natural Language Processing Conference, pages 1-8, Philadelphia, USA.
    • (2002) Proceedings of the Empirical Methods in Natural Language Processing Conference , pp. 1-8
    • Collins, M.1
  • 15
    • 0033281425 scopus 로고    scopus 로고
    • Large margin classification using the perceptron algorithm
    • Yoav Freund and Robert Schapire. 1999. Large Margin Classification Using the Perceptron Algorithm. Machine Learning, 37(3):277-296.
    • (1999) Machine Learning , vol.37 , Issue.3 , pp. 277-296
    • Freund, Y.1    Schapire, R.2
  • 17
    • 0002192516 scopus 로고
    • Decision theoretic generalizations of the PAC model for neural net and other learning applications
    • David Haussler. 1992. Decision Theoretic Generalizations of the PAC Model for Neural Net and other Learning Applications. Information and Computation, 100(1):78-150.
    • (1992) Information and Computation , vol.100 , Issue.1 , pp. 78-150
    • Haussler, D.1
  • 20
    • 0001553979 scopus 로고
    • Toward efficient agnostic learning
    • Michael Kearns, Robert Schapire, and Linda Sellie. 1994. Toward Efficient Agnostic Learning. Machine Learning, 17(2):115-141.
    • (1994) Machine Learning , vol.17 , Issue.2 , pp. 115-141
    • Kearns, M.1    Schapire, R.2    Sellie, L.3
  • 24
    • 0346986305 scopus 로고    scopus 로고
    • Shallow parsing using noisy and non-stationary training material
    • Miles Osborne. 2002. Shallow Parsing Using Noisy and Non-Stationary Training Material. Journal of Machine Learning Research, 2:695-719.
    • (2002) Journal of Machine Learning Research , vol.2 , pp. 695-719
    • Osborne, M.1
  • 26
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    • Reliability measurement without limit
    • Dennis Reidsma and Jean Carletta. 2008. Reliability measurement without limit. Computational Linguistics, 34(3):319-326.
    • (2008) Computational Linguistics , vol.34 , Issue.3 , pp. 319-326
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  • 32
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    • Games with a purpose
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    • Von Ahn, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.