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<Paper uid="P05-2001">
  <Title>Hybrid Methods for POS Guessing of Chinese Unknown Words</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes a hybrid model that combines a rule-based model with two statistical models for the task of POS guessing of Chinese unknown words. The rule-based model is sensitive to the type, length, and internal structure of unknown words, and the two statistical models utilize contextual information and the likelihood for a character to appear in a particular position of words of a particular length and POS category. By combining models that use different sources of information, the hybrid model achieves a precision of 89%, a significant improvement over the best result reported in previous studies, which was 69%.</Paragraph>
  </Section>
class="xml-element"></Paper>