We describe a machine learning system for the recognition of names in biomedical texts. The system makes extensive use of local and syntactic features within the text, as well as external resources including the web and gazetteers. It achieves an Fscore of 70% on the Coling 2004 NLPBA/BioNLP shared task of identifying five biomedical named entities in the GENIA corpus.
Finkel J.R., Nguyen H., Manning C., Dingare S., Nissim M., Sinclair G. (2004). Exploiting Context for Biomedical Entity Recognition: from Syntax to the Web. GENEVA : s.n.
Exploiting Context for Biomedical Entity Recognition: from Syntax to the Web
NISSIM, MALVINA;
2004
Abstract
We describe a machine learning system for the recognition of names in biomedical texts. The system makes extensive use of local and syntactic features within the text, as well as external resources including the web and gazetteers. It achieves an Fscore of 70% on the Coling 2004 NLPBA/BioNLP shared task of identifying five biomedical named entities in the GENIA corpus.File in questo prodotto:
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