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<Paper uid="C96-1086">
  <Title>Inherited Feature-based Similarity Measure Based on Large Semantic Hierarchy and Large Text Corpus</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We describe a similarity calculation model called IFSM (Inherited Feature Similarity Measure) between objects (words/concepts) based on their common and distinctive features. We propose an implementation method for obtaining features based on abstracted triples extracted fi'om a large text eorpus utilizing taxonomical knowledge. This model represents an integration of traditional methods, i.e,. relation b~used sin&gt; itarity measure and distribution based similarity measure. An experiment, using our new concept abstraction method which we &lt;'all the fiat probability grouping method, over 80,000 surface triples, shows that the abstraction level of 3000 is a good basis for feature description.</Paragraph>
  </Section>
class="xml-element"></Paper>