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<Paper uid="P99-1080">
  <Title>A Pylonic Decision-Tree Language Model with Optimal Question Selection</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper discusses a decision-tree approach to the problem of assigning probabilities to words following a given text. In contrast with previous decision-tree language model attempts, an algorithm for selecting nearly optimal questions is considered. The model is to be tested on a standard task, The Wall Street Journal, allowing a fair comparison with the well-known tri-gram model.</Paragraph>
  </Section>
class="xml-element"></Paper>