时空数据中时变特征的图解可视化

Xiangyang Wu , Zixi Chen , Yuhui Gu , Weiru Chen , Mei-e Fang
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引用次数: 6

摘要

识别和分析时变特征对于理解时空数据集非常重要。虽然有许多关于说明性可视化的研究,但现有的解决方案很难在时间数据集中显示出细微的变化。本文介绍了一种新的说明性可视化方案,该方案采用时间滤波技术来揭示所需的微小特征,并通过自适应时间说明技术进一步增强了这些特征。不关心的上下文可以以类似的方式被抑制。我们开发了一个视觉探索系统,使用户能够交互式地操作和分析时间特征。在手机通话数据上的实验结果证明了该方法的有效性和实用性。
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Illustrative visualization of time-varying features in spatio-temporal data

Identifying and analyzing the time-varying features is important for understanding the spatio-temporal datasets. While there are numerous studies on illustrative visualization, existing solutions can hardly show subtle variations in a temporal dataset. This paper introduces a novel illustrative visualization scheme that employs temporal filtering techniques to disclose desired tiny features, which are further enhanced by an adaptive temporal illustration technique. The unconcerned context can be suppressed in a similar fashion. We develop a visual exploration system that empowers users to interactively manipulate and analyze temporal features. The experimental results on a mobile calling data demonstrate the effectivity and usefulness of our method.

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来源期刊
Journal of Visual Languages and Computing
Journal of Visual Languages and Computing 工程技术-计算机:软件工程
CiteScore
1.62
自引率
0.00%
发文量
0
审稿时长
26.8 weeks
期刊介绍: The Journal of Visual Languages and Computing is a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of visual languages and its implication to the art of computing. The journal publishes research papers, state-of-the-art surveys, and review articles in all aspects of visual languages.
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