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<Paper uid="P94-1010">
  <Title>REFERENCES</Title>
  <Section position="9" start_page="71" end_page="71" type="concl">
    <SectionTitle>
CONCLUSIONS
</SectionTitle>
    <Paragraph position="0"> In this paper we have shown that good performance can be achieved on Chinese word segmentation by using probabilistic methods incorporated into a uniform stochastic finite-state model. We believe that the approach reported here compares favorably with other reported approaches, though obviously it is impossible to make meaningful comparisons in the absence of uniform test databases for Chinese segmentation. Perhaps the single most important difference between our work and previous work is the form of the evaluation. As we have observed there is often no single right answer to word segmentation in Chinese. Therefore, claims to the effect that a particular algorithm gets 99% accuracy are meaningless without a clear definition of accuracy.</Paragraph>
  </Section>
class="xml-element"></Paper>