<?xml version="1.0" standalone="yes"?>
<Paper uid="W06-0118">
  <Title>Voting between Dictionary-based and Subword Tagging Models for Chinese Word Segmentation</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes a Chinese word segmentation system that is based on majority voting among three models: a forward maximum matching model, a conditional random field (CRF) model using maximum subword-based tagging, and a CRF model using minimum subword-based tagging. In addition, it contains a post-processing component to deal with inconsistencies. Testing on the closed track of CityU, MSRA and UPUC corpora in the third SIGHAN Chinese Word Segmentation Bakeoff, the system achieves a F-score of 0.961, 0.953 and 0.919, respectively. null</Paragraph>
  </Section>
class="xml-element"></Paper>