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<Paper uid="C96-2099">
  <Title>Segmenting Sentences into Linky Strings Using D-bigram Statistics</Title>
  <Section position="7" start_page="689" end_page="689" type="concl">
    <SectionTitle>
6 CONCLUSION
</SectionTitle>
    <Paragraph position="0"> This paper shows that this automatic segmenting system /NS is quite efficient for segmentation of non-separated language sentences. /AN does not use any grammatical information to divide input sentences into linky strings, that is, a new refit for NLP. According to the results of the experiments, LcxC/~ can segment ahnost all the sentences 'correctly', with strings keeping their meanings.</Paragraph>
    <Paragraph position="1"> This remarkable result of a statistic-based system l~ shows that d-bigram statistical information can be a key to meaningful-string extracting. This result also shows that the concept of linky strings is an interesting concept for NLP. We expect that this linky string can he a unit for machine translation systems or key word/phrase extraction systems, and other NLP systems.</Paragraph>
  </Section>
class="xml-element"></Paper>