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<Paper uid="W97-0803">
  <Title>Extending a thesaurus by classifying words</Title>
  <Section position="11" start_page="401" end_page="401" type="concl">
    <SectionTitle>
8 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper proposed a method for extending an existing thesaurus by classifying new words in terms of that thesaurus. We conducted experiments using the Japanese Bunruigoihy5 thesaurus and about 420,000 co-occurrence pairs of verbs and nouns, related by the WO postposition. Our experiments showed that new words can be classified correctly with a maximum accuracy of more than 80% when the category-based search strategy was used.</Paragraph>
    <Paragraph position="1"> We only used co-occurrence data including the WO relation (accusative case). However, as mentioned in comparison with Uramoto's work, the use of other relations should be investigated.</Paragraph>
    <Paragraph position="2"> This paper focused on only 5 digit class codes. This is mainly because of the data sparseness of co-occurrence data. We would be able to classify words at deeper levels if we obtained more co-occurrence data. Another approach would be to construct a hierarchy from a set of words of each class, using a clustering algorithm.</Paragraph>
    <Paragraph position="3"> 5Nakano's original work used an old version of BGH, which contains 36,263 words.</Paragraph>
  </Section>
class="xml-element"></Paper>