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Volumn , Issue , 2014, Pages 211-219

Frame semantic tree kernels for social network extraction from text

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; EXTRACTION; FORESTRY; SEMANTICS;

EID: 84905677002     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (22)
  • 6
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Chris Burges. 1998. A tutorial on support vector machines for pattern recognition. Data mining and knowledge discovery.
    • (1998) Data Mining and Knowledge Discovery
    • Burges, C.1
  • 7
    • 84866866270 scopus 로고    scopus 로고
    • Semafor: Frame argument resolution with log-linear models
    • Uppsala, Sweden, July. Association for Computational Linguistics
    • Desai Chen, Nathan Schneider, Dipanjan Das, and Noah A. Smith. 2010. Semafor: Frame argument resolution with log-linear models. In Proceedings of the 5th International Workshop on Semantic Evaluation, pages 264-267, Uppsala, Sweden, July. Association for Computational Linguistics.
    • (2010) th International Workshop on Semantic Evaluation , pp. 264-267
    • Chen, D.1    Schneider, N.2    Das, D.3    Smith, N.A.4
  • 8
    • 33646057547 scopus 로고    scopus 로고
    • New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron
    • Association for Computational Linguistics
    • Michael Collins and Nigel Duffy. 2002. New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron. In Proceedings of the 40th annual meeting on association for computational linguistics, pages 263-270. Association for Computational Linguistics.
    • (2002) th Annual Meeting on Association for Computational Linguistics , pp. 263-270
    • Collins, M.1    Duffy, N.2
  • 15
    • 85140744814 scopus 로고    scopus 로고
    • Combining lexical, syntactic, and semantic features with maximum entropy models for extracting relations
    • Association for Computational Linguistics
    • Nanda Kambhatla. 2004. Combining lexical, syntactic, and semantic features with maximum entropy models for extracting relations. In Proceedings of the ACL 2004 on Interactive poster and demonstration sessions, page 22. Association for Computational Linguistics.
    • (2004) Proceedings of the ACL 2004 on Interactive Poster and Demonstration Sessions , pp. 22
    • Kambhatla, N.1
  • 17
    • 34547975798 scopus 로고    scopus 로고
    • Efficient convolution kernels for dependency and constituent syntactic trees
    • Alessandro Moschitti. 2006. Efficient convolution kernels for dependency and constituent syntactic trees. In Proceedings of the 17th European Conference on Machine Learning.
    • (2006) th European Conference on Machine Learning
    • Moschitti, A.1
  • 19
    • 84907345507 scopus 로고    scopus 로고
    • Embedding semantic similarity in tree kernels for domain adaptation of relation extraction
    • Long Papers), Sofia, Bulgaria, August. Association for Computational Linguistics
    • Barbara Plank and Alessandro Moschitti. 2013. Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1498-1507, Sofia, Bulgaria, August. Association for Computational Linguistics.
    • (2013) stAnnual Meeting of the Association for Computational Linguistics , vol.1 , pp. 1498-1507
    • Plank, B.1    Moschitti, A.2
  • 22
    • 84859917836 scopus 로고    scopus 로고
    • Extracting relations with integrated information using kernel methods
    • Shubin Zhao and Ralph Grishman. 2005. Extracting relations with integrated information using kernel methods. In Proceedings of the 43rd Meeting of the ACL.
    • (2005) rd Meeting of the ACL
    • Zhao, S.1    Grishman, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.