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Explanation of Similarities in Process-Oriented Case-Based Reasoning by Visualization

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Case-Based Reasoning Research and Development (ICCBR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14141))

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Abstract

Modeling similarity measures in Case-Based Reasoning is a knowledge-intensive, demanding, and error-prone task even for domain experts. Visualizations offer support for users, but are currently only available for certain subdomains and case representations. Currently, there are only visualizations that can be used for local attributes or specific case representations. However, there is no possibility to visualize similarities between complete processes accordingly so far, although complex domains may be present. Therefore, an extension of existing approaches or the design of new suitable concepts for this application domain is necessary. The contribution of this work is to enable a more profound understanding of similarity for knowledge engineers who create a similarity model and support them in this task by using visualization methods in Process-Oriented Case-Based Reasoning (POCBR). For this purpose, we present related approaches and evaluate them against derived requirements for visualizations in POCBR. On this basis, suitable visualizations are further developed as well as new approaches designed. Three such visualizations are created: (1) a graph mapping approach, (2) a merge graph, and (3) a visualization based on heatmaps. An evaluation of these approaches has been performed based on the requirements in which the domain experts determine the graph-mapping visualization as best-suited for engineering of similarity models.

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Notes

  1. 1.

    A detailed description of all visualization approaches, including various mock-ups, is available at https://git.opendfki.de/easy/explanation-of-similarities-in-pocbr-by-visualization/-/blob/main/Detailed_Description_of_Visualization_Approaches.pdf.

  2. 2.

    The implementation is available at https://git.opendfki.de/easy/explanation-of-similarities-in-pocbr-by-visualization.

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Acknowledgments

This work is funded by the Federal Ministry for Economic Affairs and Climate Action under grant No. 01MD22002C EASY.

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Authors and Affiliations

  1. German Research Center for Artificial Intelligence (DFKI), Branch University of Trier, Behringstraße 21, 54296, Trier, Germany

    Alexander Schultheis, Maximilian Hoffmann, Lukas Malburg & Ralph Bergmann

  2. Artificial Intelligence and Intelligent Information Systems, University of Trier, 54296, Trier, Germany

    Maximilian Hoffmann, Lukas Malburg & Ralph Bergmann

Authors
  1. Alexander Schultheis
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  2. Maximilian Hoffmann
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  3. Lukas Malburg
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  4. Ralph Bergmann
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Correspondence to Alexander Schultheis .

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Editors and Affiliations

  1. Robert Gordon University, Aberdeen, UK

    Stewart Massie

  2. Indian Institute of Technology Madras, Chennai, Tamil Nadu, India

    Sutanu Chakraborti

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Schultheis, A., Hoffmann, M., Malburg, L., Bergmann, R. (2023). Explanation of Similarities in Process-Oriented Case-Based Reasoning by Visualization. In: Massie, S., Chakraborti, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2023. Lecture Notes in Computer Science(), vol 14141. Springer, Cham. https://doi.org/10.1007/978-3-031-40177-0_4

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