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<Paper uid="C96-2212">
  <Title>Hierarchical Clustering of Words</Title>
  <Section position="6" start_page="1161" end_page="1161" type="concl">
    <SectionTitle>
4 Conclusion
</SectionTitle>
    <Paragraph position="0"> We presented an algorithm for hierarchical &lt;:has: tering of words, and conducted a clustering experiment using large texts of:varying sizes. High qtmlity of the obtained clusters are confirmed by the POS tagging experiments. By introducing word bits into the ATR l)ecision-Tree POS Tagger, the tagging error rate is reduced by up to 43%. The hierarchical clusters obtained fi'orn WSJ texts are also shown to be usefld \['or tagging ATR texts which are fi'om quite different domMns than WSJ texts.</Paragraph>
  </Section>
class="xml-element"></Paper>