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<Paper uid="P06-2056">
  <Title>Unsupervised Segmentation of Chinese Text by Use of Branching Entropy</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We propose an unsupervised segmentation method based on an assumption about language data: that the increasing point of entropy of successive characters is the location of a word boundary. A large-scale experiment was conducted by using 200 MB of unsegmented training data and 1 MB of test data,and precision of90%wasattained with recall being around 80%. Moreover, we found that the precision was stable at around 90% independently of the learning data size.</Paragraph>
  </Section>
class="xml-element"></Paper>