Exploration of Preference Models using Visual Analytics

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2024
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Deutsche Forschungsgemeinschaft (DFG): 455910360
Institutionen der Bundesrepublik Deutschland: VIKING (13N16242)
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CUEPAQ: Visual Analytics und Linguistik für Erfassen, Verständnis und Erklärung personalisierter Argumentqualität , Schwerpunktprogramm "RATIO"
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ARCHAMBAULT, Daniel, Hrsg., Ian NABNEY, Hrsg., Jaakko PELTONEN, Hrsg.. MLVis: Machine Learning Methods in Visualisation for Big Data (2024). Eindhoven: Eurographics, 2024. Verfügbar unter: doi: 10.2312/mlvis.20241127
Zusammenfassung

The identification and integration of diverse viewpoints are key to sound decision-making. This paper introduces a novel Visual Analytics technique aimed at summarizing and comparing perspectives derived from established preference models. We use 2D projection and interactive visualization to explore user models based on subjective preference labels and extracted linguistic features. We then employ a pie-chart-like exploration design to enable the aggregation and simultaneous exploration of diverse preference groupings. The approach allows rotation and slicing interactions of the visual space. We demonstrate the technique's applicability and effectiveness through a use case in exploring the complex landscape of argument preferences. We highlight our designs potential to enhance decision-making processes within diverging preferences through Visual Analytics.

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MLVis: Machine Learning Methods in Visualisation for Big Data (2024), 24. Mai 2024, Odense, Denmark
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ISO 690BUCHMÜLLER, Raphael, Mark-Matthias ZYMLA, Daniel A. KEIM, Miriam BUTT, Rita SEVASTJANOVA, 2024. Exploration of Preference Models using Visual Analytics. MLVis: Machine Learning Methods in Visualisation for Big Data (2024). Odense, Denmark, 24. Mai 2024. In: ARCHAMBAULT, Daniel, Hrsg., Ian NABNEY, Hrsg., Jaakko PELTONEN, Hrsg.. MLVis: Machine Learning Methods in Visualisation for Big Data (2024). Eindhoven: Eurographics, 2024. Verfügbar unter: doi: 10.2312/mlvis.20241127
BibTex
@inproceedings{Buchmuller2024Explo-70141,
  year={2024},
  doi={10.2312/mlvis.20241127},
  title={Exploration of Preference Models using Visual Analytics},
  publisher={Eurographics},
  address={Eindhoven},
  booktitle={MLVis: Machine Learning Methods in Visualisation for Big Data (2024)},
  editor={Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
  author={Buchmüller, Raphael and Zymla, Mark-Matthias and Keim, Daniel A. and Butt, Miriam and Sevastjanova, Rita}
}
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