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<Paper uid="P06-1047">
  <Title>Extractive Summarization using Interand Intra- Event Relevance</Title>
  <Section position="6" start_page="400" end_page="400" type="concl">
    <SectionTitle>
5. Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we propose to integrate event-based approaches to extractive summarization.</Paragraph>
    <Paragraph position="1"> Both inter-event and intra-event relevance are investigated and PageRank algorithm is used to evaluate the significance of each concept (including both event terms and named entities).</Paragraph>
    <Paragraph position="2"> The sentences containing more concepts and highest significance scores are chosen in the summary as long as they are not the same sentences. null To derive event relevance, we consider the associations at the syntactic, semantic and contextual levels. An important finding on the DUC 2001 data set is that making use of named entity relevance derived from the event terms they associate with achieves the best result. The result of 0.35212 significantly outperforms the one reported in the closely related work whose average is below 0.3. We are interested in the issue of how to improve an event representation in order to build a more powerful event-based summarization system. This would be one of our future directions. We also want to see how concepts rather than sentences are selected into the summary in order to develop a more flexible compression technique and to know what characteristics of a document set is appropriate for applying event-based summarization techniques.</Paragraph>
  </Section>
class="xml-element"></Paper>