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<Paper uid="W06-3805">
  <Title>A Study of Two Graph Algorithms in Topic-driven Summarization</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We study how two graph algorithms apply to topic-driven summarization in the scope of Document Understanding Conferences. The DUC 2005 and 2006 tasks were to summarize into 250 words a collection of documents on a topic consisting of a few statements or questions.</Paragraph>
    <Paragraph position="1"> Our algorithms select sentences for extraction. We measure their performance on the DUC 2005 test data, using the Summary Content Units made available after the challenge. One algorithm matches a graph representing the entire topic against each sentence in the collection. The other algorithm checks, for pairs of open-class words in the topic, whether they can be connected in the syntactic graph of each sentence. Matching performs better than connecting words, but a combination of both methods works best. They also both favour longer sentences, which makes summaries more uent.</Paragraph>
  </Section>
class="xml-element"></Paper>