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<Paper uid="P05-1070">
  <Title>Instance-based Sentence Boundary Determination by Optimization for Natural Language Generation</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes a novel instance-based sentence boundary determination method for natural language generation that optimizes a set of criteria based on examples in a corpus. Compared to existing sentence boundary determination approaches, our work offers three significant contributions. First, our approach provides a general domain independent framework that effectively addresses sentence boundary determination by balancing a comprehensive set of sentence complexity and quality related constraints.</Paragraph>
    <Paragraph position="1"> Second, our approach can simulate the characteristics and the style of naturally occurring sentences in an application domain since our solutions are optimized based on their similarities to examples in a corpus. Third, our approach can adapt easily to suit a natural language generation system's capability by balancing the strengths and weaknesses of its sub-components (e.g. its aggregation and referring expression generation capability).</Paragraph>
    <Paragraph position="2"> Our final evaluation shows that the proposed method results in significantly better sentence generation outcomes than a widely adopted approach.</Paragraph>
  </Section>
class="xml-element"></Paper>