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Volumn , Issue , 2009, Pages 37-42

A Comparison of Structural Correspondence Learning and Self-training for Discriminative Parse Selection

Author keywords

[No Author keywords available]

Indexed keywords

SELECTION MODEL; SELF-TRAINING; SELF-TRAINING TECHNIQUES; SEMI-SUPERVISED; SIMPLE++; WIKIPEDIA;

EID: 84896934820     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (14)
  • 2
    • 27844439373 scopus 로고    scopus 로고
    • A framework for learning predictive structures from multiple tasks and unlabeled data
    • Rie Kubota Ando and Tong Zhang. 2005. A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6:1817–1853.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 1817-1853
    • Ando, Rie Kubota1    Zhang, Tong2
  • 4
    • 84860524227 scopus 로고    scopus 로고
    • Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
    • 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.
    • (2007) Association for Computational Linguistics
    • Blitzer, John1    Dredze, Mark2    Pereira, Fernando3
  • 7
    • 84859905757 scopus 로고    scopus 로고
    • Self-training for biomedical parsing
    • Columbus, Ohio, June. Association for Computational Linguistics
    • David McClosky and Eugene Charniak. 2008. Self-training for biomedical parsing. In Proceedings of ACL-08: HLT, Short Papers, pages 101–104, Columbus, Ohio, June. Association for Computational Linguistics.
    • (2008) Proceedings of ACL-08: HLT, Short Papers , pp. 101-104
    • McClosky, David1    Charniak, Eugene2
  • 11
    • 84860518415 scopus 로고    scopus 로고
    • Self-training for enhancement and domain adaptation of statistical parsers trained on small datasets
    • Prague
    • Roi Reichart and Ari Rappoport. 2007. Self-training for enhancement and domain adaptation of statistical parsers trained on small datasets. In Proceedings of Association for Computational Linguistics, Prague.
    • (2007) Proceedings of Association for Computational Linguistics
    • Reichart, Roi1    Rappoport, Ari2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.