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<Paper uid="C04-1007">
  <Title>Combining Hierarchical Clustering and Machine Learning to Predict High-Level Discourse Structure</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We propose a novel method to predict the inter-paragraph discourse structure of text, i.e. to infer which paragraphs are related to each other and form larger segments on a higher level. Our method combines a clustering algorithm with a model of segment &amp;quot;relatedness&amp;quot; acquired in a machine learning step. The model integrates information from a variety of sources, such as word co-occurrence, lexical chains, cue phrases, punctuation, and tense. Our method outperforms an approach that relies on word co-occurrence alone.</Paragraph>
  </Section>
class="xml-element"></Paper>