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<Paper uid="W02-1903">
  <Title>A Reliable Indexing Method for a Practical QA System</Title>
  <Section position="5" start_page="21" end_page="21" type="concl">
    <SectionTitle>
4 Conclusion
</SectionTitle>
    <Paragraph position="0"> We presented a fast and high-precision QA system using a predictive answer indexer in Korean. The predictive answer indexer extracts answer candidates and terms adjacent to the candidates on the indexing time. Then, using the 2-pass scoring method, the indexer stores each candidate with the adjacent terms that have specific scores in the answer DB. On the retrieval time, the QA system just calculates the similarities between a user's query and the answer candidates. Therefore, the QA system minimizes the retrieval time and enhances the precision. Moreover, our system can easily converted into other domains because it is based on shallow NLP and IR techniques such as POS tagging, NE recognizing, pattern matching and term weighting with TF[?]IDF.</Paragraph>
  </Section>
class="xml-element"></Paper>