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<Paper uid="W97-0305">
  <Title>Detecting Subject Boundaries Within Text: A Language Independent Statistical Approach</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We describe here an algorithm for detecting subject boundaries within text based on a statistical lexical similarity measure.</Paragraph>
    <Paragraph position="1"> Hearst has already tackled this problem with good results (Hearst, 1994). One of her main assumptions is that a change in subject is accompanied by a change in vocabulary. Using this assumption, but by introducing a new measure of word significance, we have been able to build a robust and reliable algorithm which exhibits improved accuracy without sacrificing language independency.</Paragraph>
  </Section>
class="xml-element"></Paper>