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Predicting intent behind selections in scatterplot visualizations
Information Visualization ( IF 2.3 ) Pub Date : 2021-08-18 , DOI: 10.1177/14738716211038604
Kiran Gadhave 1 , Jochen Görtler 2 , Zach Cutler 1 , Carolina Nobre 3 , Oliver Deussen 2 , Miriah Meyer 1 , Jeff M. Phillips 1 , Alexander Lex 1
Affiliation  

Predicting and capturing an analyst’s intent behind a selection in a data visualization is valuable in two scenarios: First, a successful prediction of a pattern an analyst intended to select can be used to auto-complete a partial selection which, in turn, can improve the correctness of the selection. Second, knowing the intent behind a selection can be used to improve recall and reproducibility. In this paper, we introduce methods to infer analyst’s intents behind selections in data visualizations, such as scatterplots. We describe intents based on patterns in the data, and identify algorithms that can capture these patterns. Upon an interactive selection, we compare the selected items with the results of a large set of computed patterns, and use various ranking approaches to identify the best pattern for an analyst’s selection. We store annotations and the metadata to reconstruct a selection, such as the type of algorithm and its parameterization, in a provenance graph. We present a prototype system that implements these methods for tabular data and scatterplots. Analysts can select a prediction to auto-complete partial selections and to seamlessly log their intents. We discuss implications of our approach for reproducibility and reuse of analysis workflows. We evaluate our approach in a crowd-sourced study, where we show that auto-completing selection improves accuracy, and that we can accurately capture pattern-based intent.



中文翻译:

在散点图可视化中预测选择背后的意图

在数据可视化中预测和捕捉分析师在选择背后的意图在两种情况下是有价值的:首先,分析师打算选择的模式的成功预测可用于自动完成部分选择,这反过来又可以改善选择的正确性。其次,了解选择背后的意图可用于提高召回率和可重复性。在本文中,我们介绍了在数据可视化(例如散点图)中推断分析师意图背后的方法。我们根据数据中的模式描述意图,并确定可以捕获这些模式的算法。通过交互式选择,我们将所选项目与大量计算模式的结果进行比较,并使用各种排名方法来确定分析师选择的最佳模式。我们存储注释和元数据以在来源图中重建选择,例如算法类型及其参数化。我们提出了一个原型系统,它为表格数据和散点图实现了这些方法。分析师可以选择一个预测来自动完成部分选择并无缝记录他们的意图。我们讨论了我们的方法对分析工作流程的重现性和重用的影响。我们在一项众包研究中评估了我们的方法,我们表明自动完成选择提高了准确性,并且我们可以准确地捕获基于模式的意图。分析师可以选择一个预测来自动完成部分选择并无缝记录他们的意图。我们讨论了我们的方法对分析工作流程的重现性和重用的影响。我们在一项众包研究中评估了我们的方法,我们表明自动完成选择提高了准确性,并且我们可以准确地捕获基于模式的意图。分析师可以选择一个预测来自动完成部分选择并无缝记录他们的意图。我们讨论了我们的方法对分析工作流程的重现性和重用的影响。我们在一项众包研究中评估了我们的方法,我们表明自动完成选择提高了准确性,并且我们可以准确地捕获基于模式的意图。

更新日期:2021-08-19
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