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.
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.
The implementation is available at https://git.opendfki.de/easy/explanation-of-similarities-in-pocbr-by-visualization.
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This work is funded by the Federal Ministry for Economic Affairs and Climate Action under grant No. 01MD22002C EASY.
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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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