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<Paper uid="W06-0137">
  <Title>Chinese Word Segmentation based on an Approach of Maximum Entropy Modeling</Title>
  <Section position="7" start_page="203" end_page="203" type="concl">
    <SectionTitle>
4 Conclusion
</SectionTitle>
    <Paragraph position="0"> We propose an approach to Chinese word segmentation by using Maximum Entropy model, which focuses on the nexus relationship of any 2 adjacent MSUs in a text fragment. We tested our system with pure Maximum Entropy models and models with simplex classification method.</Paragraph>
    <Paragraph position="1"> Compare with the pure models, the models with classified MSUs show us better performances.</Paragraph>
    <Paragraph position="2"> However, the Maximum Entropy models of our system still need improvement if we want to achieve higher performance. In future works, we will consider using more training data and add some hybrid methods with pre- and postprocesses to improve the system.</Paragraph>
  </Section>
class="xml-element"></Paper>