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<Paper uid="W06-1319">
  <Title>Balancing Con icting Factors in Argument Interpretation</Title>
  <Section position="10" start_page="141" end_page="141" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have offered a probabilistic approach to the interpretation of arguments that casts the selection of an interpretation as a model selection task. In so doing, our formalism balances con icting factors: model complexity against data t, and structure complexity against belief reasonableness. We have demonstrated the use of our basic formalism for the selection of an interpretation graph, and shown how a more complex model and additional background knowledge account respectively for the inclusion of suppositions and explanatory extensions in an interpretation. Our user evaluations show that the interpretation graphs produced by our formalism are generally acceptable, and that there is strong support for the suppositions and explanatory extensions it proposes.</Paragraph>
  </Section>
class="xml-element"></Paper>