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<Paper uid="W04-1010">
  <Title>Template-Filtered Headline Summarization</Title>
  <Section position="8" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Conclusion and Future Work
</SectionTitle>
    <Paragraph position="0"> Generating summaries with headline-length restriction is hard because of the difficulty of squeezing a full text into a few words in a readable fashion. In practice, it often happens in order to achieve the optimal informativeness, grammatical structure is overlooked, and vice versa. In this paper, we have described a system that was designed to use two methods, individually had exhibited exactly one of the two types of unbalances, and integrated them to yield content and grammaticality. null Structural abstraction at the POS level is shown to be helpful in our current experiment. However, part-of-speech tags do not generalize well and fail to model issues like subcategorization and other lexical semantic effects. This problem was seen from the fact that there are half as many templates as the original headlines. A more refined pattern language, for example taking into account named entity types and verb clusters, will further improve performance. We intend to incorporate additional natural language processing tools to create a more sophisticated and richer hierarchical structure for headline summarization.</Paragraph>
  </Section>
class="xml-element"></Paper>