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TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data
Information Visualization ( IF 1.8 ) Pub Date : 2019-07-03 , DOI: 10.1177/1473871619858937
Aurea Soriano-Vargas 1 , Bernd Hamann 2 , Maria Cristina F de Oliveira 3
Affiliation  

We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights. We consolidated the considered analysis and visualization methods in one framework, called TV-MV Analytics. TV-MV Analytics effectively combines visualization and data mining algorithms providing the following capabilities: (1) visual exploration of multivariate data at different temporal scales, and (2) a hierarchical small multiples visualization combined with interactive clustering and multidimensional projection to detect temporal relationships in the data. We demonstrate the value of our framework for specific scenarios, by studying three use cases that were validated and discussed with domain experts.

中文翻译:

TV-MV 分析:用于探索时变多元数据的可视化分析框架

我们提出了一个集成的交互式框架,用于时变多元数据集的可视化分析。作为我们研究的一部分,我们对可视化技术的适用性进行了深入研究,以获得有价值的见解。我们将所考虑的分析和可视化方法整合到一个称为 TV-MV 分析的框架中。TV-MV Analytics 有效地结合了可视化和数据挖掘算法,提供了以下功能:(1) 在不同时间尺度上对多元数据的可视化探索,以及 (2) 分层小倍数可视化结合交互式聚类和多维投影来检测时间关系数据。我们展示了我们的框架对特定场景的价值,
更新日期:2019-07-03
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