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Natural Language Processing methods and systems for biomedical ontology learning

Liu, K and Hogan, WR and Crowley, RS (2011) Natural Language Processing methods and systems for biomedical ontology learning. Journal of Biomedical Informatics, 44 (1). 163 - 179. ISSN 1532-0464

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Abstract

While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of Natural Language Processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies. © 2010.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Liu, K
Hogan, WR
Crowley, RS
Date: 1 February 2011
Date Type: Publication
Journal or Publication Title: Journal of Biomedical Informatics
Volume: 44
Number: 1
Page Range: 163 - 179
DOI or Unique Handle: 10.1016/j.jbi.2010.07.006
Schools and Programs: School of Medicine > Biomedical Informatics
Refereed: Yes
ISSN: 1532-0464
Article Type: Review
MeSH Headings: Biomedical Research; Computational Biology; Data Mining--methods; Natural Language Processing; Vocabulary, Controlled
Other ID: NLM NIHMS224441, NLM PMC2990796
PubMed Central ID: PMC2990796
PubMed ID: 20647054
Date Deposited: 29 Aug 2012 21:05
Last Modified: 03 Feb 2019 00:55
URI: http://d-scholarship.pitt.edu/id/eprint/13824

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