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Volumn , Issue , 2006, Pages 509-516

Empirical study on the performance stability of named entity recognition model across domains

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS;

EID: 70350685696     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1610075.1610145     Document Type: Conference Paper
Times cited : (10)

References (17)
  • 1
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    • Daniel M. Bikel, Richard L. Schwartz, and Ralph M. Weischedel. 1999. An algorithm that learns what's in a name. Machine Learning, 34(1-3):211-231.
    • (1999) Machine Learning , vol.34 , Issue.1-3 , pp. 211-231
    • Bikel, D.M.1    Schwartz, R.L.2    Weischedel, R.M.3
  • 5
    • 33646401779 scopus 로고    scopus 로고
    • Chinese word segmentation and named entity recognition: A pragmatic approach
    • Jian F. Gao, Mu Li, Anndy Wu, and Chang N., Huang. 2005. Chinese Word Segmentation and Named Entity Recognition: A Pragmatic Approach. Computational Linguisitc,31(4):531-574.
    • (2005) Computational Linguisitc , vol.31 , Issue.4 , pp. 531-574
    • Gao, J.F.1    Li, M.2    Wu, A.3    Huang, C.N.4
  • 6
    • 26444606316 scopus 로고    scopus 로고
    • Chinese named entity recognition based on multilevel linguistic features
    • Springer
    • Hong L. Guo, Jian M. Jiang, Gang Hu, and Tong Zhang. 2005. Chinese Named Entity Recognition Based on Multilevel Linguistic Features. Lecture Notes in Artificial Intelligence,3248:90-99,Springer.
    • (2005) Lecture Notes in Artificial Intelligence , vol.3248 , pp. 90-99
    • Guo, H.L.1    Jiang, J.M.2    Hu, G.3    Zhang, T.4
  • 7
    • 1642296635 scopus 로고    scopus 로고
    • Efficient support vector classifiers for named entity recognition
    • Hideki Isozaki and Hideto Kazawa. 2002. Efficient support vector classifiers for named entity recognition. In Proceedings of Coling-2002, pages 1-7.
    • (2002) Proceedings of Coling-2002 , pp. 1-7
    • Isozaki, H.1    Kazawa, H.2
  • 8
    • 36448939527 scopus 로고    scopus 로고
    • Howtogetachinesename (entity) : SSegmentation and combination issues
    • Hongyan Jing, Radu Florian, Xiaoqiang Luo, Tong Zhang, and Abraham Ittycheriah. 2003. Howtogetachinesename (entity) : Segmentation and combination issues. In EMNLP 2003, pages 200-207.
    • (2003) EMNLP 2003 , pp. 200-207
    • Jing, H.1    Florian, R.2    Luo, X.3    Zhang, T.4    Ittycheriah, A.5
  • 12
    • 26444468506 scopus 로고    scopus 로고
    • Memory-based named entity recognition using unannotated data
    • Fien De Meulder and Walter Daelemans. 2003. Memory-based named entity recognition using unannotated data. In Proceedings of CoNLL-2003, pages 208-211.
    • (2003) Proceedings of CoNLL-2003 , pp. 208-211
    • De Meulder, F.1    Daelemans, W.2
  • 13
    • 85099019865 scopus 로고    scopus 로고
    • Introduction to the conll-2003 shared task: Language independent named entity recognition
    • Walter Daelemans and Miles Osborne, editors
    • Erik F. Tjong Kim Sang and Fien De Meulder. 2003. Introduction to the conll-2003 shared task: Language independent named entity recognition. In Walter Daelemans and Miles Osborne, editors, Proceedings of CoNLL-2003, pages 142-147.
    • (2003) Proceedings of CoNLL-2003 , pp. 142-147
    • Tjong, E.F.1    Sang, K.2    De Meulder, F.3
  • 14
    • 70350693274 scopus 로고    scopus 로고
    • Multi-criteria-based active learning for named entity recognition
    • Dan Shen, Jie Zhang, Jian Su, Gou D. Zhou, and Chew L.Tan, 2004. Multi-Criteria-based Active Learning for Named Entity Recognition. Proceedings of ACL04, pages 589-596.
    • (2004) Proceedings of ACL04 , pp. 589-596
    • Shen, D.1    Zhang, J.2    Su, J.3    Zhou, G.D.4    Tan, C.L.5
  • 15
    • 80053222348 scopus 로고    scopus 로고
    • Chinese named entity recognition based on multiple features
    • Yu Z. Wu, Jun Zhao, Bo Xu, and Hao Yu. 2005. Chinese Named Entity Recognition Based on Multiple Features. Proceedings of EMNLP05, pages 427-434
    • (2005) Proceedings of EMNLP05 , pp. 427-434
    • Wu, Y.Z.1    Zhao, J.2    Xu, B.3    Yu, H.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.