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北美退伍军人节(Veterans Day),12 日无更新
arXiv 2008.09830cs.HC
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沉浸式图形可视化环境中特征值的刷取

Brushing Feature Values in Immersive Graph Visualization Environment

Hinako Sassa, Maxime Cordeil, Mitsuo Yoshida, Takayuki Itoh

摘要:

存在多种图,其中多维特征值被分配给节点。这些数据集的可视化并不是一件容易的事情,因为它们很复杂,而且往往很庞大。沉浸式分析是一种强大的方法,可以支持对此类大型复杂数据的交互式探索。最近许多关于图形可视化的研究都应用了沉浸式分析框架。然而,很少有研究沉浸式分析与输入图形相关联的多维属性的可视化。本文提出了一种新的沉浸式分析系统,支持交互式探索分配给输入图的节点的多维特征值。所提出的系统显示与特征值的尺寸相对应的标签轴,以及连接标签轴并与节点相对应的标签边。该系统支持刷操作,刷操作控制连接标签轴和图形节点的边的显示。本文介绍了可视化的例子与Twitter用户的图形数据集和评论的专家对图形数据分析。

英文摘要:

There are a variety of graphs where multidimensional feature values are assigned to the nodes. Visualization of such datasets is not an easy task since they are complex and often huge. Immersive Analytics is a powerful approach to support the interactive exploration of such large and complex data. Many recent studies on graph visualization have applied immersive analytics frameworks. However, there have been few studies on immersive analytics for visualization of multidimensional attributes associated with the input graphs. This paper presents a new immersive analytics system that supports the interactive exploration of multidimensional feature values assigned to the nodes of input graphs. The presented system displays label-axes corresponding to the dimensions of feature values, and label-edges that connect label-axes and corresponding to the nodes. The system supports brushing operations which controls the display of edges that connect a label-axis and nodes of the graph. This paper introduces visualization examples with a graph dataset of Twitter users and reviews by experts on graph data analysis.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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