<?xml version="1.0" standalone="yes"?>
<Paper uid="N06-1017">
  <Title>Unknown word sense detection as outlier detection</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We address the problem of unknown word sense detection: the identification of corpus occurrences that are not covered by a given sense inventory. We model this as an instance of outlier detection, using a simple nearest neighbor-based approach to measuring the resemblance of a new item to a training set. In combination with a method that alleviates data sparseness by sharing training data across lemmas, the approach achieves a precision of 0.77 and recall of 0.82.</Paragraph>
  </Section>
class="xml-element"></Paper>