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<Paper uid="P05-1065">
  <Title>Reading Level Assessment Using Support Vector Machines and Statistical Language Models</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Reading pro ciency is a fundamental component of language competency. However, nding topical texts at an appropriate reading level for foreign and second language learners is a challenge for teachers. This task can be addressed with natural language processing technology to assess reading level. Existing measures of reading level are not well suited to this task, but previous work and our own pilot experiments have shown the benet of using statistical language models.</Paragraph>
    <Paragraph position="1"> In this paper, we also use support vector machines to combine features from traditional reading level measures, statistical language models, and other language processing tools to produce a better method of assessing reading level.</Paragraph>
  </Section>
class="xml-element"></Paper>