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Volumn , Issue , 2013, Pages 78-85

The AI-KU system at the SPMRL 2013 shared task: Unsupervised features for dependency parsing

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84926196338     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (3)

References (26)
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  • 3
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  • 5
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    • Improving generative statistical parsing with semi-supervised word clustering
    • Association for Computational Linguistics
    • Marie Candito and Benoît Crabbé. 2009. Improving generative statistical parsing with semi-supervised word clustering. In Proceedings of the 11th International Conference on Parsing Technologies, pages 138-141. Association for Computational Linguistics.
    • (2009) Proceedings of the 11th International Conference on Parsing Technologies , pp. 138-141
    • Candito, M.1    Crabbé, B.2
  • 9
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    • A unified architecture for natural language processing: Deep neural networks with multitask learning
    • ACM
    • Ronan Collobert and Jason Weston. 2008. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proceedings of the 25th international conference on Machine learning, pages 160-167. ACM.
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    • Collobert, R.1    Weston, J.2
  • 11
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    • Dayne Freitag. 2004. Trained named entity recognition using distributional clusters. In Proceedings of EMNLP, pages 262-269.
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    • Koehn, P.1
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    • Sphere embedding: An application to part-of-speech induction
    • J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta, editors
    • Yariv Maron, Michael Lamar, and Elie Bienenstock. 2010. Sphere embedding: An application to part-of-speech induction. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta, editors, Advances in Neural Information Processing Systems 23, pages 1567-1575.
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    • Fastsubs: An efficient and exact procedure for finding the most likely lexical substitutes based on an n-gram language model
    • Nov
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.