<?xml version="1.0" standalone="yes"?>
<Paper uid="W03-0416">
  <Title>An Efficient Clustering Algorithm for Class-based Language Models</Title>
  <Section position="12" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper proposed a general, class-based probability model and described a clustering algorithm for it, which we evaluated through experiments on a disambiguation task of Japanese dependency analysis. We obtained the following results. (1) Our clustering algorithm was much more efficient than the existing method that uses the same objective function and the same kind of model. (2) It worked better as an optimization algorithm for the description length than the existing method. (3) It performed better in the test task than an existing method and another method that is similar to other existing methods.</Paragraph>
  </Section>
class="xml-element"></Paper>