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<Paper uid="P05-2014">
  <Title>Dialogue Act Tagging for Instant Messaging Chat Sessions</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Instant Messaging chat sessions are real-time text-based conversations which can be analyzed using dialogue-act models.</Paragraph>
    <Paragraph position="1"> We describe a statistical approach for modelling and detecting dialogue acts in Instant Messaging dialogue. This involved the collection of a small set of task-based dialogues and annotating them with a revised tag set. We then dealt with segmentation and synchronisation issues which do not arise in spoken dialogue.</Paragraph>
    <Paragraph position="2"> The model we developed combines naive Bayes and dialogue-act n-grams to obtain better than 80% accuracy in our tagging experiment.</Paragraph>
  </Section>
class="xml-element"></Paper>