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<Paper uid="W98-1210">
  <Title>Finding Structure via Compression</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> A statistical language model may be used to segment a data sequence by thresholding its instantaneous entropy. In this paper we describe how this process works, and we apply it to the problem of discovering separator symbols in a text. Our results show that language models which bootstrap themselves with structure found in this way undergo a reduction in perplexity. We conclude that these techniques may be useful in the design of generic grammatical inference systems.</Paragraph>
  </Section>
class="xml-element"></Paper>