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<Paper uid="W99-0628">
  <Title>PP-Attachment: A Committee Machine Approach</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper we use various methods for multiple neural network combination in tasks of prepositional phrase attachment. Experiments with aggregation functions such as unweighted and weighted average, OWA operator, Choquet integral and stacked generalization demonstrate that combining multiple networks improve the estimation of each individual neural network. Using the Ratnaparkhi data set (the complete training set and the complete test set) we obtained an accuracy score of 86.08%. In spite of the high cost in computational time of neural net training, the response time in test mode is faster than others methods.</Paragraph>
  </Section>
class="xml-element"></Paper>