Linked Life Data

17990495

Source:http://linkedlifedata.com/resource/pubmed/id/17990495

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2007-11-9
pubmed:abstractText
There has been much work devoted to the mapping, alignment, and linking of ontologies (MALO), but little has been published about how to evaluate systems that do this. A fault model for conducting fine-grained evaluations of MALO systems is proposed, and its application to the system described in Johnson et al. [15] is illustrated. Two judges categorized errors according to the model, and inter-judge agreement was calculated by error category. Overall inter-judge agreement was 98% after dispute resolution, suggesting that the model is consistently applicable. The results of applying the model to the system described in [15] reveal the reason for a puzzling set of results in that paper, and also suggest a number of avenues and techniques for improving the state of the art in MALO, including the development of biomedical domain specific language processing tools, filtering of high frequency matching results, and word sense disambiguation.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1793-5091
pubmed:author
pubmed:issnType
Print
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
233-44
pubmed:dateRevised
2011-5-23
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
A fault model for ontology mapping, alignment, and linking systems.
pubmed:affiliation
Center for Computational Pharmacology, School of Medicine, University of Colorado, Aurora, CO 80045, USA. Helen.Johnson@uchsc.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural