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Journal of Visualization
Erschienen in: Journal of Visualization 6/2019

23.09.2019 | Regular Paper

RankBrushers: interactive analysis of temporal ranking ensembles

verfasst von: Dongming Han, Jiacheng Pan, Fangzhou Guo, Xiaonan Luo, Yingcai Wu, Wenting Zheng, Wei Chen

Erschienen in: Journal of Visualization | Ausgabe 6/2019

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Abstract

Temporal ranking ensembles indicate time-evolving multivariate rankings. Such data can be commonly found in our daily life, for example, different rankings of universities (QS, ARWU, THE, and USNews) over year and those of NBA players over season. Effective analysis and tracking of rankings allow users to gain insights into the overall ranking change over time and seek the explanation for the change. This paper introduces a novel visual analytics approach for characterizing and visualizing the uncertainty, dynamics, and differences of ranking ensemble data. A novel visual design is proposed to characterize the evolution pattern, distribution, and uncertainty of a large number of temporal ranking ensembles. The evolutionary ranking ensembles are progressively explored, tracked, and compared by means of an intuitive visualization system. Two case studies and a task-driven user study conducted on real datasets demonstrate the effectiveness and feasibility of the implemented system.

Graphic abstract

Vorheriger Artikel PermVizor: visual analysis of multivariate permutations
Nächster Artikel Visual analysis of impact factors of forest pests and diseases

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Metadaten
Titel
RankBrushers: interactive analysis of temporal ranking ensembles
verfasst von
Dongming Han
Jiacheng Pan
Fangzhou Guo
Xiaonan Luo
Yingcai Wu
Wenting Zheng
Wei Chen
Publikationsdatum
23.09.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Visualization / Ausgabe 6/2019
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI
https://doi.org/10.1007/s12650-019-00598-x

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