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Theory and Applications of Relational Structures as Knowledge Instruments pp 214–230Cite as

Approximation Operators in Qualitative Data Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2929))

Abstract

A large part of qualitative data analysis is concerned with approximations of sets on the basis of relational information. In this paper, we present various forms of set approximations via the unifying concept of modal–style operators. Two examples indicate the usefulness of the approach.

Co-operation for this paper was supported by EU COST Action 274 ”Theory and Applications of Relational Structures as Knowledge Instruments” (TARSKI), www.tarski.org. Ivo Düntsch gratefully acknowledges support from the National Sciences and Engineering Research Council of Canada.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Brock University, St. Catharines, Ontario, L2S 3A1, Canada

    Ivo Düntsch & Günther Gediga

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  1. Ivo Düntsch
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  2. Günther Gediga
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Editor information

Editors and Affiliations

  1. Faculty of Philosophy, Tilburg University, P.O. Box 90153, 5000 LE, Tilburg, The Netherlands

    Harrie de Swart

  2. National Institute of Telecommunications, Warsaw

    Ewa Orłowska

  3. Institute for Software Technology, Department of Computing Science, Universität der Bundeswehr München, 85577, Neubiberg, Germany

    Gunther Schmidt

  4. Faculté Polytechnique de Mons, Rue de Houdain 9, B-7000, Mons, Belgium

    Marc Roubens

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Düntsch, I., Gediga, G. (2003). Approximation Operators in Qualitative Data Analysis. In: de Swart, H., Orłowska, E., Schmidt, G., Roubens, M. (eds) Theory and Applications of Relational Structures as Knowledge Instruments. Lecture Notes in Computer Science, vol 2929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24615-2_10

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  • DOI: https://doi.org/10.1007/978-3-540-24615-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20780-1

  • Online ISBN: 978-3-540-24615-2

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