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<?xml version="1.0" standalone="yes"?>
<Paper uid="W97-0707">
  <Title>I I I I I</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Over the years, the amount of information avmlable electromcally has grown mamfold There Is an increasing demand for automatic methods for text summarization Dommnindependent techniques for automauc summanzation by paragraph extractton have been proposed m (Salton et al, 1994, Salton et al, 1996b) In tins study, we attempt to evainate these methods by companng the automatlcally generated extracts to ones generated by humans In view of the fact that extracts generrated by two humans for the same article are surprisingly dzssmular, the performance of the automatic methods Is satisfactory Even though thin observation calls into question the feasibility of producing perfect summaries by extraction, given the unavallablhty of other effective domain-independent summarization tools, we beheve that fins m a reasonable, though imperfect, alternative</Paragraph>
  </Section>
class="xml-element"></Paper>
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