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Volumn , Issue , 2011, Pages 705-713

Dynamic and Static Prototype Vectors for Semantic Composition

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; VECTORS;

EID: 85050494677     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (39)

References (22)
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    • New York, USA
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  • 3
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    • Dice, Lee R.1
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    • Ted Dunning. 1993. Accurate Methods for the Statistics of Surprise and Coincidence. Computational Linguistics, 19(1):61-74.
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    • Dunning, Ted1
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    • Exemplar-based models for word meaning in context
    • Stroudsburg, PA, USA. Association for Computational Linguistics
    • Katrin Erk and Sebastian Padó. 2010. Exemplar-based models for word meaning in context. In Proceedings of the ACL 2010 Conference Short Papers, ACLShort'10, pages 92-97, Stroudsburg, PA, USA. Association for Computational Linguistics.
    • (2010) Proceedings of the ACL 2010 Conference Short Papers, ACLShort'10 , pp. 92-97
    • Erk, Katrin1    Padó, Sebastian2
  • 9
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    • I don't believe in word senses
    • Adam Kilgarriff. 1997. I don't believe in word senses. In Computers and the Humanities, 31(2):91-113.
    • (1997) Computers and the Humanities , vol.31 , Issue.2 , pp. 91-113
    • Kilgarriff, Adam1
  • 11
    • 84858421418 scopus 로고    scopus 로고
    • Taxonomy Learning Using Word Sense Induction
    • b pages Los Angeles, California, June. ACL
    • Ioannis P. Klapaftis and Suresh Manandhar. 2010b. Taxonomy Learning Using Word Sense Induction. In Proceedings of NAACL-HLT-2010, pages 82-90, Los Angeles, California, June. ACL.
    • (2010) Proceedings of NAACL-HLT-2010 , pp. 82-90
    • Klapaftis, Ioannis P.1    Manandhar, Suresh2
  • 13
    • 84859927665 scopus 로고    scopus 로고
    • Vector-based models of semantic composition
    • Columbus, Ohio
    • Jeff Mitchell and Mirella Lapata. 2008. Vector-based models of semantic composition. In Proceedings of ACL-08: HLT, pages 236-244, Columbus, Ohio.
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    • Inducing word senses to improve web search result clustering
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  • 16
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  • 21


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.