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<Paper uid="W00-0401">
  <Title>Concept Identification and Presentation in the Context of Technical Text Summarization</Title>
  <Section position="11" start_page="8" end_page="9" type="concl">
    <SectionTitle>
8 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper, we have presented a method of text summarization which produces indicative-informative abstracts. We have described the techniques we are using to implement our method and some experiments showing the viability of the approach.</Paragraph>
    <Paragraph position="1"> Our method was specified for summarization of one specific type of text: the scientific and technical document. Nevertheless, it is domain independent because the concepts, relations and types of information we use are common across different domains. The question of the coverage of the model will be addressed in our future work. Our method was designed without any particular reader in mind and with the assumption that a text does have a &amp;quot;main&amp;quot; topic. If readers were known, the abstract could be tailored towards their specific profiles. User profiles could be used in order to produce the informative abstracts elaborating those specific aspects the reader is &amp;quot;usually&amp;quot; interested in. This aspect will be elaborated in future work.</Paragraph>
    <Paragraph position="2"> The experiments reported here addressed  the evaluation of the indicative abstracts using a categorization task. Using the automatic abstracts reader have chosen the correct category for the articles in 70% of the cases compared with 80% of the cases when using the author abstracts. Readers found the abstracts produced by our method of better quality than a sentence-extraction based system.</Paragraph>
  </Section>
class="xml-element"></Paper>