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Selection from Overlapping Classifications

  • F. Gebhardt
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Semantic classification utilizes structural and semantical properties of data rather than purely their numerical values for constructing classes of objects. In the process of semantic interpretation of data sets, we arrive in our project EXPLORA at a collection of possible descriptions of a given goal set. We propose here a procedure for selecting certain classes from this collection. The procedure chooses them by means of their quality and of a kind of similarity, usually unsymmetric, which we call affinity. The idea is to suppress a class if it is sufficiently similar to, but also inferior to an other class that is itself retained. Some examples illustrate the method and its effect on the results.

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Bibliography

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1991

Authors and Affiliations

  • F. Gebhardt
    • 1
  1. 1.Gesellschaft für Mathematik und Datenverarbeitung mbHInstitut für Angewandte Informationstechnik Schloß BirlinghovenSankt Augustin 1Germany

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