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<Paper uid="P05-1016">
  <Title>Inducing Ontological Co-occurrence Vectors</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper, we present an unsupervised methodology for propagating lexical co-occurrence vectors into an ontology such as WordNet. We evaluate the framework on the task of automatically attaching new concepts into the ontology. Experimental results show 73.9% attachment accuracy in the first position and 81.3% accuracy in the top-5 positions. This framework could potentially serve as a foundation for ontologizing lexical-semantic resources and assist the development of other large-scale and internally consistent collections of semantic information.</Paragraph>
  </Section>
class="xml-element"></Paper>