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<Paper uid="W06-0120">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics On Closed Task of Chinese Word Segmentation: An Improved CRF Model Coupled with Character Clustering and Automatically Generated Template Matching</Title>
  <Section position="6" start_page="136" end_page="136" type="concl">
    <SectionTitle>
4 Conclusion
</SectionTitle>
    <Paragraph position="0"> The contribution of this paper is two fold. First, we successfully apply the K-means algorithm to character clustering and develop several cluster set selection algorithms for our GS tagger. This significantly improves the handling of sentences containing non-Chinese words as well as the overall performance. Second, we develop a post-processing method that compensates for the weakness of ML-based CWS on longer words.</Paragraph>
  </Section>
class="xml-element"></Paper>