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Explainable and Explorable Decision Support

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Graph-Based Representation and Reasoning (ICCS 2022)

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Abstract

An effective decision support system requires a user’s trust in its results, which are based on expected utilities of different action plans. As such, a result needs to be explainable and explorable, providing alternatives and additional information in a proactive way, instead of retroactively answering follow-up questions to a single action plan as output. Therefore, this paper presents LEEDS, an algorithm that computes alternative action plans, identifies groups of interest, and answers marginal queries for those groups to provide a comprehensive overview supporting a user. LEEDS leverages the strengths of gate models, lifting, and the switched lifted junction tree algorithm for efficient explainable and explorable decision support.

T. Braun and M. Gehrke—Both authors contributed equally to the paper.

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Notes

  1. 1.

    https://dtai.cs.kuleuven.be/software/gcfove.

  2. 2.

    https://www.ifis.uni-luebeck.de/index.php?id=518.

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Acknowledgements

The research of MG was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2176 ‘Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures’, project no. 390893796. The research was conducted within the scope of the Centre for the Study of Manuscript Cultures (CSMC) at Universität Hamburg.

Author information

Authors and Affiliations

  1. Data Science Group, University of Münster, Münster, Germany

    Tanya Braun

  2. Institute of Information Systems, University of Lübeck, Lübeck, Germany

    Marcel Gehrke

Authors
  1. Tanya Braun
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  2. Marcel Gehrke
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Correspondence to Marcel Gehrke .

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Editors and Affiliations

  1. University of Münster, Münster, Germany

    Tanya Braun

  2. Babes-Bolyai University, Cluj-Napoca, Romania

    Diana Cristea

  3. Humboldt-Universität zu Berlin, Berlin, Germany

    Robert Jäschke

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Braun, T., Gehrke, M. (2022). Explainable and Explorable Decision Support. In: Braun, T., Cristea, D., Jäschke, R. (eds) Graph-Based Representation and Reasoning. ICCS 2022. Lecture Notes in Computer Science(), vol 13403. Springer, Cham. https://doi.org/10.1007/978-3-031-16663-1_8

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  • DOI: https://doi.org/10.1007/978-3-031-16663-1_8

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  • Online ISBN: 978-3-031-16663-1

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