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<Paper uid="W03-0501">
  <Title>Hedge Trimmer: A Parse-and-Trim Approach to Headline Generation</Title>
  <Section position="10" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Conclusions and Future Work
</SectionTitle>
    <Paragraph position="0"> We have shown the effectiveness of constructing headlines by selecting words in order from a newspaper story. The practice of selecting words from the early part of the document has been justified by analyzing the behavior of humans doing the task, and by automatic evaluation of a system operating on a similar principle.</Paragraph>
    <Paragraph position="1"> We have compared two systems that use this basic technique, one taking a statistical approach and the other a linguistic approach. The results of the linguistically motivated approach show that we can build a working system with minimal linguistic knowledge and circumvent the need for large amounts of training data.</Paragraph>
    <Paragraph position="2"> We should be able to quickly produce a comparable system for other languages, especially in light of current multi-lingual initiatives that include automatic parser induction for new languages, e.g. the TIDES initiative.</Paragraph>
    <Paragraph position="3"> We plan to enhance Hedge Trimmer by using a language model of Headlinese, the language of newspaper headlines (Mardh 1980) to guide the system in which constituents to remove. We Also we plan to allow for morphological variation in verbs to produce the present tense headlines typical of Headlinese.</Paragraph>
    <Paragraph position="4"> Hedge Trimmer will be installed in a translingual detection system for enhanced display of document surrogates for cross-language question answering. This system will be evaluated in upcoming iCLEF conferences. null</Paragraph>
  </Section>
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