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<?xml version="1.0" standalone="yes"?>
<Paper uid="P99-1004">
  <Title>Measures of Distributional Similarity</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. Our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.</Paragraph>
  </Section>
class="xml-element"></Paper>
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