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Volumn 1, Issue , 2012, Pages 620-628

Bootstrapping via graph propagation

Author keywords

[No Author keywords available]

Indexed keywords

BOOTSTRAPPING ALGORITHM; LEARNING METHODS; NATURAL LANGUAGES; OBJECTIVE FUNCTIONS; PROPAGATION ALGORITHM; STATE-OF-THE-ART PERFORMANCE;

EID: 84878207820     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (18)

References (20)
  • 1
    • 18744410770 scopus 로고    scopus 로고
    • Understanding the Yarowsky algorithm
    • S. Abney. 2004. Understanding the Yarowsky algorithm. Computational Linguistics, 30(3).
    • (2004) Computational Linguistics , vol.30 , Issue.3
    • Abney, S.1
  • 6
    • 85118152899 scopus 로고    scopus 로고
    • Three generative, lexicalised models for statistical parsing
    • Madrid, Spain, July, Association for Computational Linguistics
    • Michael Collins. 1997. Three generative, lexicalised models for statistical parsing. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, pages 16-23, Madrid, Spain, July. Association for Computational Linguistics.
    • (1997) Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics , pp. 16-23
    • Collins, M.1
  • 12
    • 0012990385 scopus 로고
    • Automatic acquisition of hyponyms from large text corpora
    • Stroudsburg, PA, USA. Association for Computational Linguistics
    • Marti A. Hearst. 1992. Automatic acquisition of hyponyms from large text corpora. In Proceedings of the 14th conference on Computational linguistics - Volume 2, COLING '92, pages 539-545, Stroudsburg, PA, USA. Association for Computational Linguistics.
    • (1992) Proceedings of the 14th Conference on Computational Linguistics - Volume 2, COLING '92 , pp. 539-545
    • Hearst, M.A.1
  • 14
    • 0033886806 scopus 로고    scopus 로고
    • Text classification from labeled and unlabeled documents using EM
    • K. Nigam, A. McCallum, S. Thrun, and T. Mitchell. 2000. Text classification from labeled and unlabeled documents using EM. Machine Learning, 30(3).
    • (2000) Machine Learning , vol.30 , Issue.3
    • Nigam, K.1    McCallum, A.2    Thrun, S.3    Mitchell, T.4
  • 16
    • 38049094034 scopus 로고
    • Probability of error of some adaptive pattern-recognition machines
    • H. J. Scudder. 1965. Probability of error of some adaptive pattern-recognition machines. IEEE Transactions on Information Theory, 11:363-371.
    • (1965) IEEE Transactions on Information Theory , vol.11 , pp. 363-371
    • Scudder, H.J.1
  • 17
    • 79952257762 scopus 로고    scopus 로고
    • Efficient graph-based semi-supervised learning of structured tagging models
    • Cambridge, MA, October. Association for Computational Linguistics
    • Amarnag Subramanya, Slav Petrov, and Fernando Pereira. 2010. Efficient graph-based semi-supervised learning of structured tagging models. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 167-176, Cambridge, MA, October. Association for Computational Linguistics.
    • (2010) Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing , pp. 167-176
    • Subramanya, A.1    Petrov, S.2    Pereira, F.3
  • 20
    • 85141919230 scopus 로고
    • Unsupervised word sense disambiguation rivaling supervised methods
    • Cambridge, Massachusetts, USA, June, Association for Computational Linguistics
    • David Yarowsky. 1995. Unsupervised word sense disambiguation rivaling supervised methods. In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics, pages 189-196, Cambridge, Massachusetts, USA, June. Association for Computational Linguistics.
    • (1995) Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics , pp. 189-196
    • Yarowsky, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.