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Relevance Matrix Generation Using Sensitivity Analysis in a Case-Based Reasoning Environment

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Case-Based Reasoning Research and Development (ICCBR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9969))

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Abstract

Relevance matrices are a way to formalize the contribution of each attribute in a classification task. Within the CBR paradigm these matrices can be used to improve the global similarity function that outputs the similarity degree of two cases, which helps facilitate retrieval. In this work a sensitivity analysis method was developed to optimize the relevance values of each attribute of a case in a CBR environment, thus allowing an improved comparison of cases. The process begins with a statistical analysis of the values in a given dataset, and continues with an incremental update of the relevance of each attribute.

The method was tested on two datasets and it was shown that the statistical analysis performs better than evenly distributed relevance values, making it a suitable initial setting for the incremental update, and that updating the values over time gives better results than the statistical analysis.

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Notes

  1. 1.

    http://archive.ics.uci.edu/ml.

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Author information

Authors and Affiliations

  1. Knowledge Management Group, German Research Center for Artificial Intelligence, Kaiserslautern, Germany

    Rotem Stram, Pascal Reuss & Klaus-Dieter Althoff

  2. Institute of Computer Science, Intelligent Information Systems Lab, University of Hildesheim, Hildesheim, Germany

    Pascal Reuss & Klaus-Dieter Althoff

  3. Airbus Operations GmbH, Kreetslag 10, 21129, Hamburg, Germany

    Wolfram Henkel & Daniel Fischer

Authors
  1. Rotem Stram
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  2. Pascal Reuss
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  3. Klaus-Dieter Althoff
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  4. Wolfram Henkel
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  5. Daniel Fischer
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Corresponding author

Correspondence to Rotem Stram .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology , Atlanta, Georgia, USA

    Ashok Goel

  2. Universidad Complutense de Madrid , Madrid, Spain

    M Belén Díaz-Agudo

  3. University of West London , London, United Kingdom

    Thomas Roth-Berghofer

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Stram, R., Reuss, P., Althoff, KD., Henkel, W., Fischer, D. (2016). Relevance Matrix Generation Using Sensitivity Analysis in a Case-Based Reasoning Environment. In: Goel, A., Díaz-Agudo, M., Roth-Berghofer, T. (eds) Case-Based Reasoning Research and Development. ICCBR 2016. Lecture Notes in Computer Science(), vol 9969. Springer, Cham. https://doi.org/10.1007/978-3-319-47096-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-47096-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47095-5

  • Online ISBN: 978-3-319-47096-2

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