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<Paper uid="W04-3247">
  <Title>LexPageRank: Prestige in Multi-Document Text Summarization</Title>
  <Section position="6" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have presented a novel approach to define sentence centrality based on graph-based prestige scoring of sentences. Constructing the similarity graph of sentences provides us with a better view of important sentences compared to the centroid approach, which is prone to overgeneralization of the information in a document cluster. We have introduced two different methods, Degree and LexPageRank, for computing prestige in similarity graphs. The results of applying these methods on extractive summarization is quite promising. Even the simplest approach we have taken, degree centrality, is a good enough heuristic to perform better than lead-based and centroid-based summaries.</Paragraph>
  </Section>
class="xml-element"></Paper>