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<Paper uid="W00-1106">
  <Title>Corpus-Based Learning of Compound Noun Indexing *</Title>
  <Section position="7" start_page="63" end_page="64" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we presented a method to extract the compound noun indexing rules automatically from a large tagged corpus, and showed that this method can index compound nouns appearing in diverse types of documents. null In the view of effectiveness, this method is slightly better than the previous linguistic approaches but requires no human effort.</Paragraph>
    <Paragraph position="1"> The proposed method also uses no parser and no rules described by humans, therefore, it can be applied to unrestricted texts very robustly and has high domain porta- null bility. We also presented a filtering method to solve the compound noun over-generation problem. Our proposed filtering method (H) shows good retrieval performance both in the view of the effectiveness and the efficiency. In the future, we need to perform some experiments on much larger commercial databases to test the practicality of our method.</Paragraph>
    <Paragraph position="2"> . Finally, our method doesn't require language dependent knowledge, so it needs to be verified whether it can be easily applied to other languages.</Paragraph>
  </Section>
class="xml-element"></Paper>