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GlyphLink: An interactive visualization approach for semantic graphs

机译:GlyphLink:语义图的交互式可视化方法

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Graph analysis by data visualization involves achieving a series of topology-based tasks. When the graph data belongs to a data domain that contains multiple node and link types, as in the case of semantic graphs, topology-based tasks become more challenging. To reduce visual complexity in semantic graphs, we propose an approach which is based on applying relational operations such as selecting and joining nodes of different types. We use node aggregation to reflect the relational operations to the graph. We introduce glyphs for representing aggregated nodes. Using glyphs lets us encode connectivity information of multiple nodes with a single glyph. We also use visual parameters of the glyph to encode node attributes or type specific information. Rather than doing the operations in the data abstraction layer and presenting the user with the resulting visualization, we propose an interactive approach where the user can iteratively apply the relational operations directly on the visualization. We present the efficiency of our method by the results of a usability study that includes a case study on a subset of the International Movie Database. The results of the controlled experiment in our usability study indicate a statistically significant contribution in reducing the completion time of the evaluation tasks.
机译:通过数据可视化进行图形分析涉及完成一系列基于拓扑的任务。当图数据属于包含多个节点和链接类型的数据域时(如语义图的情况),基于拓扑的任务变得更具挑战性。为了减少语义图中的视觉复杂性,我们提出了一种基于应用关系操作(例如选择和连接不同类型的节点)的方法。我们使用节点聚合将关系操作反映到图。我们介绍了表示聚合节点的字形。使用字形可以让我们使用单个字形编码多个节点的连接信息。我们还使用字形的视觉参数来编码节点属性或键入特定信息。我们提出了一种交互式方法,而不是在数据抽象层中进行操作并向用户提供结果可视化,而是让用户可以在可视化上直接迭代地应用关系操作。我们通过可用性研究的结果来介绍我们方法的效率,该研究包括对国际电影数据库的子集的案例研究。在我们的可用性研究中,受控实验的结果表明,在减少评估任务的完成时间方面,具有统计学上的重大贡献。

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