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<Paper uid="W98-0317">
  <Title>Cue Phrase Selection in Instruction Dialogue Using Machine Learning</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> The purpose of this paper is to identify effective factors for selecting discourse organization cue phrases in instruction dialogue that signal changes in discourse structure such as topic shifts and attentional state changes. By using a machine learning technique, a variety of features concerning discourse structure, task structure, and dialogue context are examined in terms of their effectiveness and the best set of learning &lt;features is identified. Our result reveals that, in addition to discourse structure, already identified in previous studies, task structure and dialogue context play an important role. Moreover, an evaluation using a large dialogue corpus shows the utihty of applying machine learning techniques to cue phrase selection.</Paragraph>
  </Section>
class="xml-element"></Paper>