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POSBIOTM-NER: a trainable biomedical named-entity recognition system.

Yu Song·Eunju Kim·Gary Geunbae Lee·Byoung-Kee Yi
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Abstract

SUMMARY: POSBIOTM-NER is a trainable biomedical named-entity recognition system. POSBIOTM-NER can be automatically trained and adapted to new datasets without performance degradation, using CRF (conditional random field) machine learning techniques and automatic linguistic feature analysis. Currently, we have trained our system on three different datasets. GENIA-NER was trained based on GENIA Corpus, GENE-NER based on BioCreative data and GPCR-NER based on our own POSBIOTM/NE corpus, respectively, which would be used in GPCR-related pathway extraction.

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AlgorithmsArtificial IntelligenceBiomedical ResearchNatural Language ProcessingPattern Recognition, AutomatedPeriodicals as TopicSoftwareTerminology as TopicVocabulary, ControlledJournal ArticleResearch Support, Non-U.S. Gov't

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Yu Song, Eunju Kim, Gary Geunbae Lee, Byoung-Kee Yi. 2005-04-06. POSBIOTM-NER: a trainable biomedical named-entity recognition system.. https://doi.org/10.1093/bioinformatics%2Fbti414

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