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<Paper uid="W00-1305">
  <Title>Topic Analysis Using a Finite Mixture Model</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We address the issue of 'topic analysis,' by which is determined a text's topic structure, which indicates what topics are included in a text, and how topics change within the text.</Paragraph>
    <Paragraph position="1"> We propose a novel approach to this issue, one based on statistical modeling and learning.</Paragraph>
    <Paragraph position="2"> We represent topics by means of word clusters, and employ a finite mixture model to represent a word distribution within a text. Our experimental results indicate that our method significantly outperforms a method that combines existing techniques.</Paragraph>
  </Section>
class="xml-element"></Paper>