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Volumn , Issue , 2007, Pages 57-64

Annotation of chemical named entities

Author keywords

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Indexed keywords

TRANSLATION (LANGUAGES);

EID: 84901002352     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1572392.1572403     Document Type: Conference Paper
Times cited : (64)

References (19)
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  • 4
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    • A system for identifying named entities in biomedical text: How results from two evaluations reflect on both the system and the evaluations
    • Shipra Dingare, Malvina Nissim, Jenny Finkel, Christopher Manning and Claire Grover. 2005. A system for identifying named entities in biomedical text: how results from two evaluations reflect on both the system and the evaluations. Comparative and Functional Ge-nomics, 6(1-2),77-85.
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  • 5
    • 11344294871 scopus 로고    scopus 로고
    • Extraction of Information from the Text of Chemical Patents. 1. Identification of Specific Chemical Names
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    • (1998) J. Chem. Inf. Comput. Sci. , vol.38 , pp. 544-551
    • Kemp, N.1    Lynch, M.2
  • 6
    • 4944229711 scopus 로고    scopus 로고
    • GENIA corpus—a semantically annotated corpus for bio-textmining
    • J.-D. Kim, T. Ohta, Y. Tateisi and J. Tsujii. 2003. GENIA corpus—a semantically annotated corpus for bio-textmining. Bioinformatics, 19(Suppl 1):i180-i182.
    • (2003) Bioinformatics , vol.19 , pp. i180-i182
    • Kim, J.-D.1    Ohta, T.2    Tateisi, Y.3    Tsujii, J.4
  • 11
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    • Using Automatically Learnt Verb Selectional Preferences for Classification of Biomedical Terms
    • Irena Spasic and Sophia Ananiadou. 2004. Using Automatically Learnt Verb Selectional Preferences for Classification of Biomedical Terms. Journal of Biomedical Informatics, 37(6):483-497.
    • (2004) Journal of Biomedical Informatics , vol.37 , Issue.6 , pp. 483-497
    • Spasic, I.1    Ananiadou, S.2
  • 13
    • 8444237887 scopus 로고    scopus 로고
    • Using Unlabeled MEDLINE Abstracts for Biological Named Entity Classification
    • Manabu Torii and K. Vijay-Shanker. 2002. Using Unlabeled MEDLINE Abstracts for Biological Named Entity Classification. Genome Informatics, 13:567-568.
    • (2002) Genome Informatics , vol.13 , pp. 567-568
    • Torii, M.1    Vijay-Shanker, K.2
  • 14
    • 8444245919 scopus 로고    scopus 로고
    • Using name-internal and contextual features to classify biological terms
    • Manabu Torii, Sachin Kamboj and K. Vijay-Shanker. 2004. Using name-internal and contextual features to classify biological terms. Journal of Biomedical Informatics, 37:498-511.
    • (2004) Journal of Biomedical Informatics , vol.37 , pp. 498-511
    • Torii, M.1    Kamboj, S.2    Vijay-Shanker, K.3
  • 16
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    • Identifying Chemical Names in Biomedical Text: An Investigation of the Substring Co-occurence Based Approaches
    • Alexander Vasserman. 2004. Identifying Chemical Names in Biomedical Text: An Investigation of the Substring Co-occurence Based Approaches. Proceedings of the Student Research Workshop at HLT-NAACL. 7-12.
    • (2004) Proceedings of The Student Research Workshop at HLT-NAACL , pp. 7-12
    • Vasserman, A.1
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    • Bootstrapping and Evaluating Named Entity Recognition in the Biomedical Domain
    • Andreas Vlachos and Caroline Gasperin. 2006. Bootstrapping and Evaluating Named Entity Recognition in the Biomedical Domain. Proceedings of BioNLP in HLT-NAACL. 138-145.
    • (2006) Proceedings of BioNLP in HLT-NAACL , pp. 138-145
    • Vlachos, A.1    Gasperin, C.2
  • 19
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    • BioCreAtIvE Task IA: Gene mention finding evaluation
    • Alexander Yeh, Alexander Morgan, Marc Colosimo and Lynette Hirschman. 2005. BioCreAtIvE Task IA: gene mention finding evaluation. BMC Bioinformatics 6(Suppl I):S2.
    • (2005) BMC Bioinformatics , vol.6 , pp. S2
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.