Performance of named entity recognition using using partial matching for ME+BS in machine learning labeler and priority list in resolution module.

Nigel Collier (45987)
Mai-vu Tran (470277)
Hoang-quynh Le (470278)
Quang-Thuy Ha (470279)
Anika Oellrich (158637)
Dietrich Rebholz-Schuhmann (46499)

Publication date

October 2013

DOI

10.1371/journal.pone.0072965.t006

Abstract

<p>Each horizontal row shows a combination of features and the associated F-scores for each class on test data. <i>ALL</i> shows micro-averaged F-score. Key to external resources: J: JNLPBA model, U: UMLS and MetaMap, H: Human Phenotype Ontology, M: Mammalian Phenotype Ontology, G: Gene Dictionary from NCBI, L: Linnaeus, F: Foundation Model of Anatomy, P: Phenotypic Trait Ontology, C: Jochem's dictionary, B: Brenda Tissue Ontology.</p

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Performance of named entity recognition using using partial matching for ME+BS in machine learning labeler and priority list in resolution module.

Abstract

Extracted data

Performance of named entity recognition using using partial matching for ME+BS in machine learning labeler and priority list in resolution module.

Abstract

Extracted data

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