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Volumn , Issue , 2010, Pages 28-36

Automatic domain adaptation for parsing

Author keywords

[No Author keywords available]

Indexed keywords

DIFFERENT DOMAINS; DOCUMENT COLLECTION; DOMAIN ADAPTATION; HETEROGENEOUS DOMAINS; LINEAR COMBINATIONS; MULTIPLE SOURCE; QUANTITATIVE MEASURES; STATISTICAL PARSER;

EID: 84863395582     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (142)

References (26)
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  • 3
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    • Prague, Czech Republic
    • John Blitzer, Mark Dredze, and Fernando Pereira. 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In Association for Computational Linguistics, Prague, Czech Republic.
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    • Blitzer, J.1    Dredze, M.2    Pereira, F.3
  • 4
    • 80053251519 scopus 로고    scopus 로고
    • TAG, dynamic programming, and the perceptron for efficient, feature-rich parsing
    • Manchester, England, August
    • Xavier Carreras, Michael Collins, and Terry Koo. 2008. TAG, dynamic programming, and the perceptron for efficient, feature-rich parsing. In Proceedings of CoNLL 2008, pages 9-16, Manchester, England, August.
    • (2008) Proceedings of CoNLL 2008 , pp. 9-16
    • Carreras, X.1    Collins, M.2    Koo, T.3
  • 5
    • 84859885240 scopus 로고    scopus 로고
    • Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
    • Eugene Charniak and Mark Johnson. 2005. Coarse-to-fine n-best parsing and MaxEnt discriminative reranking. In Proceedings of the ACL 2005, pages 173-180.
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    • Charniak, E.1    Johnson, M.2
  • 8
    • 84860513476 scopus 로고    scopus 로고
    • Frustratingly easy domain adaptation
    • Prague, Czech Republic
    • Hal Daumé III. 2007. Frustratingly easy domain adaptation. In Proceedings of ACL 2007, Prague, Czech Republic.
    • (2007) Proceedings of ACL 2007
    • Daumé III, H.1
  • 9
    • 79951490162 scopus 로고    scopus 로고
    • Online methods for multi-domain learning and adaptation
    • Honolulu, Hawaii, October
    • Mark Dredze and Koby Crammer. 2008. Online methods for multi-domain learning and adaptation. In Proceedings of the EMNLP 2008, pages 689-697, Honolulu, Hawaii, October.
    • (2008) Proceedings of the EMNLP 2008 , pp. 689-697
    • Dredze, M.1    Crammer, K.2
  • 10
    • 79959818548 scopus 로고    scopus 로고
    • Hierarchical Bayesian domain adaptation
    • Boulder, Colorado, June
    • Jenny Rose Finkel and Christopher D. Manning. 2009. Hierarchical bayesian domain adaptation. In Proceedings of HLT-NAACL 2009, pages 602-610, Boulder, Colorado, June.
    • (2009) Proceedings of HLT-NAACL 2009 , pp. 602-610
    • Finkel, J.R.1    Manning, C.D.2
  • 11
    • 84943783874 scopus 로고    scopus 로고
    • Parser evaluation and the bnc: Evaluating 4 constituency parsers with 3 metrics
    • Marrakech, Morocco, May
    • Jennifer Foster and Josef van Genabith. 2008. Parser evaluation and the bnc: Evaluating 4 constituency parsers with 3 metrics. In Proceedings LREC 2008, Marrakech, Morocco, May.
    • (2008) Proceedings LREC 2008
    • Foster, J.1    Van Genabith, J.2
  • 17
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    • Building a large annotated corpus of English: The penn treebank
    • Mitchell P. Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz. 1993. Building a large annotated corpus of English: The Penn Treebank. Comp. Linguistics, 19(2):313-330.
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  • 19
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    • Reranking and self-training for parser adaptation
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    • David McClosky, Eugene Charniak, and Mark Johnson. 2006b. Reranking and self-training for parser adaptation. In Proceedings of COLING-ACL 2006, pages 337-344, Sydney, Australia, July. Association for Computational Linguistics.
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    • McClosky, D.1    Charniak, E.2    Johnson, M.3
  • 25
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    • An empirical study of semi-supervised structured conditional models for dependency parsing
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    • Jun Suzuki, Hideki Isozaki, Xavier Carreras, and Michael Collins. 2009. An empirical study of semi-supervised structured conditional models for dependency parsing. In Proceedings EMNLP 2009, pages 551-560, Singapore, August.
    • (2009) Proceedings EMNLP 2009 , pp. 551-560
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.