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<Paper uid="W05-1302">
  <Title>Adaptive String Similarity Metrics for Biomedical Reference Resolution</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> 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.</Paragraph>
    <Paragraph position="1"> 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. null</Paragraph>
  </Section>
class="xml-element"></Paper>