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Volumn , Issue , 2013, Pages 27-30

Combining dictionaries and ontologies for drug name recognition in biomedical texts

Author keywords

Drug named entity recognition; Information extraction

Indexed keywords

BIOMEDICAL TEXT; COMBINED SYSTEM; DOMAIN SPECIFIC; EXACT MATCHING; NAME RECOGNITION; NAMED ENTITY RECOGNITION; ONTOLOGY-BASED; SEMANTIC KNOWLEDGE;

EID: 84889610386     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2512089.2512100     Document Type: Conference Paper
Times cited : (12)

References (10)
  • 1
    • 0035752429 scopus 로고    scopus 로고
    • Effective mapping of biomedical text to the umls metathesaurus: The metamap program
    • American Medical Informatics Association
    • A. R. Aronson. Effective mapping of biomedical text to the umls metathesaurus: the metamap program. In Proceedings of the AMIA Symposium, page 17. American Medical Informatics Association, 2001.
    • (2001) Proceedings of the AMIA Symposium , pp. 17
    • Aronson, A.R.1
  • 2
    • 84889582645 scopus 로고    scopus 로고
    • University of Turku in the ddiextraction 2013 task
    • Association for Computational Linguistics, June
    • J. Björne, S. Kaewphan, and T. Salakoski. University of turku in the ddiextraction 2013 task. In Proceedings of SemEval 2013, pages 341-350. Association for Computational Linguistics, June 2013.
    • (2013) Proceedings of SemEval 2013 , pp. 341-350
    • Björne, J.1    Kaewphan, S.2    Salakoski, T.3
  • 4
    • 84947926499 scopus 로고    scopus 로고
    • Lasige: Using conditional random fields and chebi ontology
    • Association for Computational Linguistics, June
    • T. Grego, F. Pinto, and F. Couto. Lasige: Using conditional random fields and chebi ontology. In Proceedings of SemEval 2013, page 660-666. Association for Computational Linguistics, June 2013.
    • (2013) Proceedings of SemEval 2013 , pp. 660-666
    • Grego, T.1    Pinto, F.2    Couto, F.3
  • 5
    • 84889588244 scopus 로고    scopus 로고
    • Wbi-ner: The impact of domain-specific features on the performance of identifying and classifying mentions of drugs
    • Association for Computational Linguistics, June
    • T. Rocktäschel, T. Huber, M. Weidlich, and U. Leser. Wbi-ner: The impact of domain-specific features on the performance of identifying and classifying mentions of drugs. In Proceedings of SemEval 2013, pages 356-363. Association for Computational Linguistics, June 2013.
    • (2013) Proceedings of SemEval 2013 , pp. 356-363
    • Rocktäschel, T.1    Huber, T.2    Weidlich, M.3    Leser, U.4
  • 6
    • 84863506694 scopus 로고    scopus 로고
    • Chemspot: A hybrid system for chemical named entity recognition
    • April
    • T. Rocktäschel, M. Weidlich, and U. Leser. Chemspot: a hybrid system for chemical named entity recognition. Bioinformatics, 28(12):1633-1640, April 2012.
    • (2012) Bioinformatics , vol.28 , Issue.12 , pp. 1633-1640
    • Rocktäschel, T.1    Weidlich, M.2    Leser, U.3
  • 7
    • 84998590769 scopus 로고    scopus 로고
    • Uem-uc3m: An ontology-based named entity recognition system for biomedical texts
    • Association for Computational Linguistics, June
    • D. Sanchez-Cisneros and F. Aparicio. Uem-uc3m: An ontology-based named entity recognition system for biomedical texts. In Proceedings of SemEval 2013, pages 622-627. Association for Computational Linguistics, June 2013.
    • (2013) Proceedings of SemEval 2013 , pp. 622-627
    • Sanchez-Cisneros, D.1    Aparicio, F.2
  • 9
    • 84938578107 scopus 로고    scopus 로고
    • Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)
    • Association for Computational Linguistics, June
    • I. Segura-Bedmar, P. Martínez, and M. Herrero-Zazo. Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013). In Proceedings of SemEval 2013, page 341-350. Association for Computational Linguistics, June 2013.
    • (2013) Proceedings of SemEval 2013 , pp. 341-350
    • Segura-Bedmar, I.1    Martínez, P.2    Herrero-Zazo, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.