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<Paper uid="C04-1187">
  <Title>Web-Based List Question Answering</Title>
  <Section position="7" start_page="5" end_page="5" type="concl">
    <SectionTitle>
8 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have presented the techniques used in FADA, a system which aims to find complete and distinct answers on the Web using question parsing, web page classification/clustering and content extraction. By using the novel approach, we can achieve a recall of 0.422 and F  of 0.464, which is significantly better than the top performing systems in the TREC-12 List QA task. The method has been found to be effective. Our future work includes discovering answers on non-text web information, such as images. Much text information is stored as images on the web, and hence, cannot be accessed by our approach, and some do contain valuable information.</Paragraph>
  </Section>
class="xml-element"></Paper>