论文标题
沉浸式图可视化环境中的刷牙特征值
Brushing Feature Values in Immersive Graph Visualization Environment
论文作者
论文摘要
在各种图中，将多维特征值分配给节点。此类数据集的可视化并不是一件容易的事，因为它们很复杂并且通常很大。沉浸式分析是一种支持这种大型和复杂数据的交互式探索的有力方法。关于图形可视化的许多最新研究都应用了沉浸式分析框架。然而，对于与输入图相关的多维属性可视化的沉浸式分析的研究很少。本文提出了一个新的沉浸式分析系统，该系统支持分配给输入图节点的多维特征值的交互式探索。呈现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缘。该系统支持刷牙操作，该操作控制着连接图形的标签轴和节点的边缘的显示。本文使用Twitter用户的图数据集介绍了可视化示例，并由专家进行了图形数据分析的评论。
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.
