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<Paper uid="C04-1067">
  <Title>Chinese and Japanese Word Segmentation Using Word-Level and Character-Level Information</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we presented a hybrid method for word segmentation, which utilizes both word-level and character-level information to obtain high accuracy for known and unknown words. The method combines two existing methods, the Markov model-based method and character tagging method. Experimental results showed that the method achieves high accuracy compared to the other state-of-the-art methods in both Chinese and Japanese word segmentation. The method can conduct POS tagging for known words as well as word segmentation, but tagging identified unknown words is left as future work.</Paragraph>
  </Section>
class="xml-element"></Paper>