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<Paper uid="P95-1017">
  <Title>Evaluating Automated and Manual Acquisition of Anaphora Resolution Strategies</Title>
  <Section position="9" start_page="295" end_page="295" type="concl">
    <SectionTitle>
6 Summary and Future Work
</SectionTitle>
    <Paragraph position="0"> This paper compared our automated and manual acquisition of anaphora resolution strategies, and reported optimistic results for the former. We plan to continue to improve machine learning-based system performance by introducing other relevant features. For example, discourse structure information (Passonneau and Litman, 1993; Hearst, 1994), if obtained reliably and automatically, will be another useful domain-independent feature. In addition, we will explore the possibility of combining machine learning results with manual encoding of discourse knowledge. This can be accomplished by allowing the user to interact with the produced classifters, tracing decisions back to particular examples and allowing users to edit features and to evaluate the efficacy of changes.</Paragraph>
  </Section>
class="xml-element"></Paper>