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Convexity in Ordinal Data

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Classification, Data Analysis, and Knowledge Organization

Abstract

Convexity is a leading idea in data analysis, although it is mostly involved on an informal level; in particular, convexity in ordinal data has not been elaborated as a well defined tool. This paper presents a first discussion of convexity definitions in connection with examples of ordinal data. One result is that there is more than one definition of ordinal convexity which is meaningful for data analysis. Convexity in multi-varied ordinal data is analysed by methods of formal concept analysis. Some relation to Euclidean convexity is outlined.

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References

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Author information

Authors and Affiliations

  1. Forschungsgruppe Begriffsanalyse Fachbereich Mathematik, Technische Hochschule Darmstadt, Schloßgartenstr. 7, D-6100, Darmstadt, Germany

    Selma Strahringer & Rudolf Wille

Authors
  1. Selma Strahringer
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  2. Rudolf Wille
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Editor information

Editors and Affiliations

  1. Institut für Statistik und Wirtschaftsmathematik, Rheinisch-Westfälische Technische Hochschule Aachen, Wüllnerstraße 3, D-5100, Aachen, Germany

    Hans-Hermann Bock

  2. Institut für Medizinische Biometrie, Philipps-Universität Marburg, Bunsenstraße 3, D-3500, Marburg, Germany

    Peter Ihm

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© 1991 Springer-Verlag Berlin · Heidelberg

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Strahringer, S., Wille, R. (1991). Convexity in Ordinal Data. In: Bock, HH., Ihm, P. (eds) Classification, Data Analysis, and Knowledge Organization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76307-6_16

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  • DOI: https://doi.org/10.1007/978-3-642-76307-6_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53483-9

  • Online ISBN: 978-3-642-76307-6

  • eBook Packages: Springer Book Archive

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