Piccolotto, N., Wallinger, M., Miksch, S., & Bögl, M. (2024). On Combined Visual Cluster and Set Analysis. In 2024 IEEE Visualization and Visual Analytics (VIS) (pp. 131–135). IEEE. https://doi.org/10.1109/VIS55277.2024.00034
Visual cluster analysis; Set Visualization; Set Analysis
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Abstract:
Real-world datasets often consist of quantitative and categorical variables. The analyst needs to focus on either kind separately or both jointly. We proposed a visualization technique tackling these challenges that supports visual cluster and set analysis. In this paper, we investigate how its visualization parameters affect the accuracy and speed of cluster and set analysis tasks in a controlled experiment. Our findings show that, with the proper settings, our visualization can support both task types well. However, we did not find settings suitable for the joint task, which provides opportunities for future research.
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Project title:
HumanE AI Network: 952026 (European Commission) Engineering Linear Ordering Algorithms for Optimizing Data Visualizations: ICT19-035 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds)
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Research Areas:
Visual Computing and Human-Centered Technology: 100%
