IEEE VIS 2024 Content: On Combined Visual Cluster and Set Analysis

On Combined Visual Cluster and Set Analysis

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 Nikolaus Piccolotto - TU Wien, Vienna, Austria

Markus Wallinger - TU Wien, Vienna, Austria

 Silvia Miksch - Institute of Visual Computing and Human-Centered Technology, Vienna, Austria

 Markus Bögl - TU Wien, Vienna, Austria

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 Room: Bayshore VI

2024-10-16T12:30:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T12:30:00Z

Exemplar figure, described by caption below — Our results show that layouts focused on multidimensional similarities supported a multidimensional cluster analysis task, layouts focused on set similarities supported set relation tasks, and neither layout supported the joint task well.

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Keywords

Visual cluster analysis, set visualization.

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.