Sequencing of categorical time series

Sequencing of categorical time series
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分类时间序列的排序

DOI:
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发表时间:
2015
期刊:
IEEE Conference on Visual Analytics Science and Technology
影响因子:
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通讯作者:
H. Schumann
H. Schumann
中科院分区:
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文献类型:
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作者:
C. Richter;M. Luboschik;Martin Rohlig;H. Schumann

文献摘要

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在时间序列数据挖掘领域,探索、比较分类时间序列和发现时间模式是一项复杂的任务。尽管存在不同的分析方法,但这些任务仍然具有挑战性,特别是当同时考虑多个时间序列时。我们提出了一种可视化分析方法,支持通过有意义的方式排序时间序列来探索这些数据。我们提供交互技术来引导自动安排,并允许用户详细调查模式。
Exploring and comparing categorical time series and finding temporal patterns are complex tasks in the field of time series data mining. Although different analysis approaches exist, these tasks remain challenging, especially when numerous time series are considered at once. We propose a visual analysis approach that supports exploring such data by ordering time series in meaningful ways. We provide interaction techniques to steer the automated arrangement and to allow users to investigate patterns in detail.