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A theoretical model for pattern discovery in visual analytics 被引量:1
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作者 Natalia Andrienko Gennady Andrienko +2 位作者 Silvia Miksch Heidrun Schumann Stefan Wrobel 《Visual Informatics》 EI 2021年第1期23-42,共20页
The word‘pattern’frequently appears in the visualisation and visual analytics literature,but what do we mean when we talk about patterns?We propose a practicable definition of the concept of a pattern in a data dist... The word‘pattern’frequently appears in the visualisation and visual analytics literature,but what do we mean when we talk about patterns?We propose a practicable definition of the concept of a pattern in a data distribution as a combination of multiple interrelated elements of two or more data components that can be represented and treated as a unified whole.Our theoretical model describes how patterns are made by relationships existing between data elements.Knowing the types of these relationships,it is possible to predict what kinds of patterns may exist.We demonstrate how our model underpins and refines the established fundamental principles of visualisation.The model also suggests a range of interactive analytical operations that can support visual analytics workflows where patterns,once discovered,are explicitly involved in further data analysis. 展开更多
关键词 Visual analytics data distribution PATTERN ABSTRACTION data organisation data arrangement data variation Pattern discovery
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