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<Paper uid="W00-1302">
  <Title>What's yours and what's mine: Determining Intellectual Attribution in Scientific Text</Title>
  <Section position="13" start_page="14" end_page="15" type="concl">
    <SectionTitle>
6 Conclusions
</SectionTitle>
    <Paragraph position="0"> Argumentative zoning is the task of breaking a text containing a scientific argument into linear zones of the same argumentative status, or zones of the same intellectual attribution. We plan to use argumentative zoning as a first step for IR and shallow document understanding tasks like summarization. In contrast to hierarchical segmentation (e.g. Marcu's (1997) work, which is based on RST (Mann and Thompson, 1987)), this type of segmentation aims at capturing the argumentative status of a piece of text in respect to the overall argumentative act of the paper. It does not deter- null individual features Precision and Recall of Automatic Processing (Naive Bayes system), per mine the rhetorical structure within zones. Subzone structure is most likely related to domain-specific rhetorical relations which are not directly relevant to the discourse-level relations we wish to recognize.</Paragraph>
    <Paragraph position="1"> We have presented a fully implemented prototype for argumentative zoning. Its main innovation are two new features: prototypical agents and actions -- semi-shallow representations of the overall scientific argumentation of the article. For agent and action recognition, we use syntactic heuristics and two extensive libraries of patterns.</Paragraph>
    <Paragraph position="2"> Processing is robust and very low in error. We evaluated the system without and with the agent and action features and found that the features improve results for automatic argumentative zoning considerably. History-aware agents are the best single feature in a large, extensively tested feature pool.</Paragraph>
  </Section>
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