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Automatic Analysis, Theme Generation, and Summarization of Machine-Readable Texts

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Information Retrieval and Hypertext

Part of the book series: Information Retrieval and Hypertext ((EPUB))

Abstract

Many kinds of texts are currently available in machine-readable form and are amenable to automatic processing. Because the available databases are large and cover many different subject areas, automatic aids must be provided to users interested in accessing the data. It has been suggested that links be placed between related pieces of text, connecting, for example, particular text paragraphs to other paragraphs covering related subject matter. Such a linked text structure, often called hypertext, makes it possible for the reader to start with particular text passages and use the linked structure to find related text elements [4, 19, 5, 12]. Unfortunately, until now, viable methods for automatically building large hypertext structures and for using such structures in a sophisticated way have not been available. Here we give methods for constructing text relation maps and for using text relations to access and use text databases. In particular, we outline procedures for determining text themes, traversing texts selectively, and extracting summary statements that reflect text content.

1 Vast amounts of text material are now available in machine-readable form for automatic processing. Here, approaches are outlined for manipulating and accessing texts in arbitrary subject areas in accordance with user needs. In particular, methods are given for determining text themes, traversing texts selectively, and extracting summary statements reflecting text content.

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Author information

Authors and Affiliations

  1. Cornell University, USA

    Gerard Salton, James Allan, Chris Buckley & Amit Singhal

Authors
  1. Gerard Salton
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  2. James Allan
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  3. Chris Buckley
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  4. Amit Singhal
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Editor information

Editors and Affiliations

  1. Department of Electronics and Informatics, University of Padua, Via Gradenigo 6/A, 35131, Padova, Italy

    Maristella Agosti

  2. School of Computer Applications, Dublin City University, Glasnevin, Dublin 9, Ireland

    Alan F. Smeaton

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© 1996 Kluwer Academic Publishers

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Salton, G., Allan, J., Buckley, C., Singhal, A. (1996). Automatic Analysis, Theme Generation, and Summarization of Machine-Readable Texts. In: Agosti, M., Smeaton, A.F. (eds) Information Retrieval and Hypertext. Information Retrieval and Hypertext. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1373-1_3

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  • DOI: https://doi.org/10.1007/978-1-4613-1373-1_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8593-9

  • Online ISBN: 978-1-4613-1373-1

  • eBook Packages: Springer Book Archive

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