Adaptive string similarity metrics for biomedical reference resolution

Authors: 
Wellner, B; Castano, J; Pustejovsky, J
Author: 
Wellner, B
Castano, J
Pustejovsky, J
Year: 
2005
Venue: 
Proc ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics
URL: 
http://acl.ldc.upenn.edu/w/w05/w05-13.pdf
Citations: 
9
Citations range: 
1 - 9
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ER-biomd.pdf159.61 KB

In this paper we present the evaluation
of a set of string similarity metrics used
to resolve the mapping from strings to
concepts in the UMLS MetaThesaurus.
String similarity is conceived as a single
component in a full Reference Resolution
System that would resolve such a mapping.
Given this qualification, we obtain
positive results achieving 73.6 F-measure
(76.1 precision and 71.4 recall) for the
task of assigning the correct UMLS concept
to a given string. Our results demonstrate
that adaptive string similarity methods
based on Conditional Random Fields
outperform standard metrics in this domain.