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<Paper uid="W97-0106">
  <Title>I I I I I, I l Grammar Acquisition Based on Clustering Analysis and Its Application to Statistical Parsing</Title>
  <Section position="7" start_page="37" end_page="39" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we proposed a method of applying clustering aaalysis to learn a context-sensitive probab'flistic grammar from an unlabeled bracketed corpus. Supported by some experiments, local contextual information which is left and right categories of a constituent was shown to be useful for acquiring a context-sensitive conditional probability context-free grammar from a corpus. A probabilistic parsing model using the acquired grammar was described and its potential was eT~m{ned. Through experiments, our parser can achieve high paxsing accuracy to some extent compared with other previous approaches with less computational cost. As our further work, there  are still many possibilities for improvement which are encouraging. For instance, it is possible to use lexical information and head information in clustering and constructing a probabilistic g~l~Yn Tn ~LY.</Paragraph>
  </Section>
class="xml-element"></Paper>