Exploration of Preference Models using Visual Analytics
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
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.
Description
CCS Concepts: Human-centered computing → Visualization design and evaluation methods
@inproceedings{10.2312:mlvis.20241127,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{Exploration of Preference Models using Visual Analytics}},
author = {Buchmüller, Raphael and Zymla, Mark-Matthias and Keim, Daniel and Butt, Miriam and Sevastjanova, Rita},
year = {2024},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-256-1},
DOI = {10.2312/mlvis.20241127}
}