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<Paper uid="W04-3252">
  <Title>TextRank: Bringing Order into Texts</Title>
  <Section position="7" start_page="54" end_page="54" type="concl">
    <SectionTitle>
6 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper, we introduced TextRank - a graph-based ranking model for text processing, and show how it can be successfully used for natural language applications. In particular, we proposed and evaluated two innovative unsupervised approaches for keyword and sentence extraction, and showed that the accuracy achieved by TextRank in these applications is competitive with that of previously proposed state-of-the-art algorithms. An important aspect of TextRank is that it does not require deep linguistic knowledge, nor domain or language specific annotated corpora, which makes it highly portable to other domains, genres, or languages.</Paragraph>
  </Section>
class="xml-element"></Paper>