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Visualizing Sequences of Texts Using Collocational Networks

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Machine Learning and Data Mining in Pattern Recognition (MLDM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2734))

Abstract

This paper presents the collocational network, a method originating in corpus linguistics, as a tool for visualizing sequences of texts. A collocational network is a two-dimensional picture of the most central words in a text and the connections between them. When collocational networks are created out of sequences of documents, they offer the user the possibility to quickly discover the most significant differences between the documents. As a case study, a sequence of financial reports is turned into collocational networks for visual comparison.

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References

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Author information

Authors and Affiliations

  1. Department of General Linguistics, University of Helsinki, P.O. Box 9, 00014, Finland

    Camilla Magnusson

  2. Pori School of Technology and Economics, Tampere University of Technology, P.O. Box 300, 28101, Pori, Finland

    Hannu Vanharanta

Authors
  1. Camilla Magnusson
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  2. Hannu Vanharanta
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, Arndtstr. 4, 04275, Leipzig, Germany

    Petra Perner

  2. Center for Automation Research, University of Maryland, College Park, Maryland, 20742-3275, USA

    Azriel Rosenfeld

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© 2003 Springer-Verlag Berlin Heidelberg

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Cite this paper

Magnusson, C., Vanharanta, H. (2003). Visualizing Sequences of Texts Using Collocational Networks. In: Perner, P., Rosenfeld, A. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2003. Lecture Notes in Computer Science, vol 2734. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45065-3_24

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  • DOI: https://doi.org/10.1007/3-540-45065-3_24

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40504-7

  • Online ISBN: 978-3-540-45065-8

  • eBook Packages: Springer Book Archive

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