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<Paper uid="E06-1036">
  <Title>Recognizing Textual Parallelisms with edit distance and similarity degree</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Detection of discourse structure is crucial in many text-based applications. This paper presents an original framework for describing textual parallelism which allows us to generalize various discourse phenomena and to propose a unique method to recognize them. With this prospect, we discuss several methods in order to identify the most appropriate one for the problem, and evaluate them based on a manually annotated corpus.</Paragraph>
  </Section>
class="xml-element"></Paper>