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Volumn , Issue , 2004, Pages 151-158

Learning noun phrase anaphoricity to improve coreference resolution: Issues in representation and optimization

Author keywords

[No Author keywords available]

Indexed keywords

COREFERENCE; COREFERENCE RESOLUTION; CORPUS-BASED APPROACHES; DATA SET; KEY ISSUES; NOUN PHRASE; OPTIMISATIONS; PERFORMANCE;

EID: 85149108413     PISSN: 0736587X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (48)

References (22)
  • 1
    • 85149114277 scopus 로고    scopus 로고
    • Corpus-based identification of non-anaphoric noun phrases
    • David Bean and Ellen Riloff. 1999. Corpus-based identification of non-anaphoric noun phrases. In Proceedings of the ACL, pages 373–380.
    • (1999) Proceedings of the ACL , pp. 373-380
    • Bean, David1    Riloff, Ellen2
  • 7
    • 84937342374 scopus 로고    scopus 로고
    • Applying machine learning toward an automatic classification of it
    • Richard Evans. 2001. Applying machine learning toward an automatic classification of it. Literary and Linguistic Computing, 16(1):45–57.
    • (2001) Literary and Linguistic Computing , vol.16 , Issue.1 , pp. 45-57
    • Evans, Richard1
  • 8
    • 0001882443 scopus 로고    scopus 로고
    • Anaphor for everyone: Pronominal anaphora resolution without a parser
    • Christopher Kennedy and Branimir Boguraev. 1996. Anaphor for everyone: Pronominal anaphora resolution without a parser. In Proceedings of COLING, pages 113–118.
    • (1996) Proceedings of COLING , pp. 113-118
    • Kennedy, Christopher1    Boguraev, Branimir2
  • 9
    • 30844441070 scopus 로고
    • An algorithm for pronominal anaphora resolution
    • Shalom Lappin and Herbert Leass. 1994. An algorithm for pronominal anaphora resolution. Computational Linguistics, 20(4):535–562.
    • (1994) Computational Linguistics , vol.20 , Issue.4 , pp. 535-562
    • Lappin, Shalom1    Leass, Herbert2
  • 13
    • 11144345567 scopus 로고    scopus 로고
    • Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution
    • a pages
    • Vincent Ng and Claire Cardie. 2002a. Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution. In Proceedings of COLING, pages 730–736.
    • (2002) Proceedings of COLING , pp. 730-736
    • Ng, Vincent1    Cardie, Claire2
  • 14
    • 85018107058 scopus 로고    scopus 로고
    • Improving machine learning approaches to coreference resolution
    • b pages
    • Vincent Ng and Claire Cardie. 2002b. Improving machine learning approaches to coreference resolution. In Proceedings of the ACL, pages 104–111.
    • (2002) Proceedings of the ACL , pp. 104-111
    • Ng, Vincent1    Cardie, Claire2
  • 16
    • 0242306667 scopus 로고
    • Towards the automatic recognition of anaphoric features in English text: the impersonal pronoun’it
    • Chris Paice and Gareth Husk. 1987. Towards the automatic recognition of anaphoric features in English text: the impersonal pronoun’it’. Computer Speech and Language, 2.
    • (1987) Computer Speech and Language , vol.2
    • Paice, Chris1    Husk, Gareth2
  • 18
    • 0039891959 scopus 로고    scopus 로고
    • A machine learning approach to coreference resolution of noun phrases
    • Wee Meng Soon, Hwee Tou Ng, and Daniel Chung Yong Lim. 2001. A machine learning approach to coreference resolution of noun phrases. Computational Linguistics, 27(4):521–544.
    • (2001) Computational Linguistics , vol.27 , Issue.4 , pp. 521-544
    • Soon, Wee Meng1    Ng, Hwee Tou2    Lim, Daniel Chung Yong3
  • 19
    • 85149123318 scopus 로고    scopus 로고
    • A machine learning approach to pronoun resolution in spoken dialogue
    • Michael Strube and Christoph Müller. 2003. A machine learning approach to pronoun resolution in spoken dialogue. In Proceedings of the ACL, pages 168–175.
    • (2003) Proceedings of the ACL , pp. 168-175
    • Strube, Michael1    Müller, Christoph2
  • 20
    • 0039925298 scopus 로고    scopus 로고
    • An empirically-based system for processing definite descriptions
    • Renata Vieira and Massimo Poesio. 2000. An empirically-based system for processing definite descriptions. Computational Linguistics, 26(4):539–593.
    • (2000) Computational Linguistics , vol.26 , Issue.4 , pp. 539-593
    • Vieira, Renata1    Poesio, Massimo2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.