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<Paper uid="P98-2189">
  <Title>Ranking Text Units According to Textual Saliency, Connectivity and Topic Aptness</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> As information systems become a more integral part of personal computing, it appears clear that summarization technology must be able to address users' needs effectively if it is to meet the demands of a growing market in the area of document management. Minimally, the abridgement of a text according to a user's needs involves selecting the most salient portions of the text which are topically best suited to represent the user's interests. This selection must also take into consideration the degree of connectivity among the chosen text portions so as to minimize the danger of producing summaries which contain poorly linked sentences. In addition, the assessment of textual saliency, connectivity and topic aptness must be computed efficiently enough so that summadeg This work was carried out within the Information Technology Group at SHARP Laboratories of Europe, Oxford, UK. I am indebted to Julian Asquith, Jan I Jdens, Ian Johnson and Victor Poznarlski for helpful comments on previous versions of this document.. Many thanks also to Stephen Burns for internet programming support., Ralf Steinberger for assistance in dictionary conversion, and Charlotte Boynton for editorial help.</Paragraph>
    <Paragraph position="1"> rization can be conveniently performed on-line.</Paragraph>
    <Paragraph position="2"> The goal of this paper is to show how these objectives can be achieved through a conceptual indexing technique based on an efficient use of lexical cohesion.</Paragraph>
  </Section>
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