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Volumn , Issue , 2009, Pages 84-85

Discriminative Models for Semi-Supervised Natural Language Learning

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EID: 77951160932     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (17)
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    • Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
    • John Blitzer, Mark Dredze, and Fernando Pereira. 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In Proceedings of the ACL.
    • (2007) Proceedings of the ACL
    • Blitzer, John1    Dredze, Mark2    Pereira, Fernando3
  • 2
    • 0031620208 scopus 로고    scopus 로고
    • Combining labeled and unlabeled data with co-training
    • Avrim Blum and Tom Mitchell. 1998. Combining labeled and unlabeled data with co-training. In Proceedings of COLT.
    • (1998) Proceedings of COLT
    • Blum, Avrim1    Mitchell, Tom2
  • 4
    • 77952316369 scopus 로고    scopus 로고
    • Lexicon acquisition for dialectal Arabic using transductive learning
    • Kevin Duh and Katrin Kirchhoff. 2006. Lexicon acquisition for dialectal Arabic using transductive learning. In Proceedings of EMNLP.
    • (2006) Proceedings of EMNLP
    • Duh, Kevin1    Kirchhoff, Katrin2
  • 7
    • 0001938951 scopus 로고    scopus 로고
    • Transductive inference for text classification using support vector machines
    • Thorsten Joachims. 1999. Transductive inference for text classification using support vector machines. In Proceedings of ICML.
    • (1999) Proceedings of ICML
    • Joachims, Thorsten1
  • 10
    • 85094067550 scopus 로고    scopus 로고
    • Weakly supervised natural language learning without redundant views
    • Vincent Ng and Claire Cardie. 2003. Weakly supervised natural language learning without redundant views. In Proceedings of HLT-NAACL.
    • (2003) Proceedings of HLT-NAACL
    • Ng, Vincent1    Cardie, Claire2
  • 11
    • 59549087165 scopus 로고    scopus 로고
    • On discriminative vs.generative classifiers: A comparison of logistic regression and Naive Bayes
    • Andrew Ng and Michael Jordan. 2002. On discriminative vs.generative classifiers: A comparison of logistic regression and Naive Bayes. In Advances in NIPS.
    • (2002) Advances in NIPS
    • Ng, Andrew1    Jordan, Michael2
  • 12
    • 2142727946 scopus 로고    scopus 로고
    • Limitations of co-training for natural language learning from large datasets
    • David Pierce and Claire Cardie. 2001. Limitations of co-training for natural language learning from large datasets. In Proceedings of EMNLP.
    • (2001) Proceedings of EMNLP
    • Pierce, David1    Cardie, Claire2
  • 16
    • 42649125186 scopus 로고    scopus 로고
    • Competitive generative models with structure learning for NLP classification tasks
    • Kristina Toutanova. 2006. Competitive generative models with structure learning for NLP classification tasks. In Proceedings of EMNLP.
    • (2006) Proceedings of EMNLP
    • Toutanova, Kristina1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.