RankBrushers: interactive analysis of temporal ranking ensembles

Han, Dongming; Pan, Jiacheng; Guo, Fei; Luo, Xiangfeng; Wu, Yingcai; Zheng, Wenting; Chen, Wei

doi:10.1007/s12650-019-00598-x

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…Gratzl et al 13 use parallel coordinates plots to visualize rankings based on different attributes. Further work on visualizing different possible rankings are provided in Behrisch et al 14 and Han et al 15 . However, we are not aware of application of any prior work in the field of challenge data analysis.…”

Section: Introductionmentioning

confidence: 99%

Methods and open-source toolkit for analyzing and visualizing challenge results

Wiesenfarth

Reinke

Landman

et al. 2021

Sci Rep

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Grand challenges have become the de facto standard for benchmarking image analysis algorithms. While the number of these international competitions is steadily increasing, surprisingly little effort has been invested in ensuring high quality design, execution and reporting for these international competitions. Specifically, results analysis and visualization in the event of uncertainties have been given almost no attention in the literature. Given these shortcomings, the contribution of this paper is two-fold: (1) we present a set of methods to comprehensively analyze and visualize the results of single-task and multi-task challenges and apply them to a number of simulated and real-life challenges to demonstrate their specific strengths and weaknesses; (2) we release the open-source framework challengeR as part of this work to enable fast and wide adoption of the methodology proposed in this paper. Our approach offers an intuitive way to gain important insights into the relative and absolute performance of algorithms, which cannot be revealed by commonly applied visualization techniques. This is demonstrated by the experiments performed in the specific context of biomedical image analysis challenges. Our framework could thus become an important tool for analyzing and visualizing challenge results in the field of biomedical image analysis and beyond.

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Section: Introductionmentioning

confidence: 99%

Methods and open-source toolkit for analyzing and visualizing challenge results

Wiesenfarth

Reinke

Landman

et al. 2021

Sci Rep

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“…LiveRAC [39] 在基于网格的布局中显示了时间序列数据的多个视图, 因此用户可以轻松地在多个细节级别上排名比较不同的序列. 如图 10 所示, Han 等 [40] 提出了一种基于热图和直方图的视觉编码方案支持用户通过悬停、刷选和过滤等交互技术, 在大规模的时间排名集合中探索数据时间序列的分布和不确定性.…”

Section: 时间序列排名可视分析unclassified

“…球迷可以通过 Podium [32] 发现最喜欢球队的重要特征, 以帮助球迷预测球队在接下来的赛季中的排名. Han 等 [40] 设计的 RankBrushers 可以对 NBA 球员在赛季中的排名进行有效的分析和跟踪, 让用户深入了解随着时间的推移整体排名的变化, 并寻求变化规律以及解释分析原因. 在传媒领域, Maheswari 等 [51] 设计的 RankTagViz 根据语义对用户游记进行排名, 并且基于标签和图像可视化旅游日志, 帮助读者获取有价值的旅游信息.…”

Section: 时间序列排名可视分析unclassified

A Survey on the Visual Analytics for Data Ranking

Zhou¹,

Cheng²,

Zhu³

et al. 2021

J Comput-Aided Design Comput Graphics

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“…Gratzl et al [GLG∗13] facilitates the exploration of multiple attributes, some of them as headers of the tables, and can visualize several occurrences up to some extent. Han et al [HPG∗19] aggregate temporal data to gain insights on the changes of rankings for basketball teams. Thus, they do not provide a narrative on a certain season.…”

Section: Related Workmentioning

confidence: 99%

TourVis: Narrative Visualization of Multi‐Stage Bicycle Races

Iriberri

Fort

Vázquez

2021

Computer Graphics Forum

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There are many multiple‐stage racing competitions in various sports such as swimming, running, or cycling. The wide availability of affordable tracking devices facilitates monitoring the position along with the race of all participants, even for non‐professional contests. Getting real‐time information of contenders is useful but also unleashes the possibility of creating more complex visualization systems that ease the understanding of the behavior of all participants during a simple stage or throughout the whole competition. In this paper we focus on bicycle races, which are highly popular, especially in Europe, being the Tour de France its greatest exponent. Current visualizations from TV broadcasting or real‐time tracking websites are useful to understand the current stage status, up to a certain extent. Unfortunately, still no current system exists that visualizes a whole multi‐stage contest in such a way that users can interactively explore the relevant events of a single stage (e.g. breakaways, groups, virtual leadership…), as well as the full competition. In this paper, we present an interactive system that is useful both for aficionados and professionals to visually analyze the development of multi‐stage cycling competitions.

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RankBrushers: interactive analysis of temporal ranking ensembles

Cited by 7 publications

References 47 publications

Methods and open-source toolkit for analyzing and visualizing challenge results

Methods and open-source toolkit for analyzing and visualizing challenge results

A Survey on the Visual Analytics for Data Ranking

TourVis: Narrative Visualization of Multi‐Stage Bicycle Races

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