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<Paper uid="P02-1064">
  <Title>An Empirical Study of Active Learning with Support Vector Machines for Japanese Word Segmentation</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
2 Support Vector Machines
</SectionTitle>
    <Paragraph position="0"> In this section we give some theoretical definitions of SVMs. Assume that we are given the training data  The decision function CV in SVM framework is defined as:</Paragraph>
    <Paragraph position="2"> where C3 is a kernel function, CQ BE CA is a threshold, and AB</Paragraph>
  </Section>
class="xml-element"></Paper>