SpEuler：语义保持的欧拉图
SpEuler: Semantics-preserving Euler Diagrams
摘要：
由于其复杂性，创建高度重叠的集合类型数据的可理解的可视化是一项具有挑战性的任务。为了便于深入了解集合的连通性，并利用交叉点之间的语义关系，我们提出了一个快速的两步布局技术，欧拉图是匹配良好，形式良好。我们的方法符合欧拉图的语义，美学和可读性的既定形式准则。首先，我们建立一个初始的数据排序，然后我们使用它来增量创建一个平面的，连接的，单调的对偶图表示。在下一步中，图被转换为圆形布局，该布局保持语义并产生具有平滑曲线的简单欧拉图。当数据不能用简单的图表表示时，我们的算法总是会回到一个格式不好但仍然匹配良好的解决方案，而以前的方法往往无法产生预期的结果。我们展示了我们的方法的实用性，可视化集类型的数据，使用文本分析和信息图表的例子。此外，我们讨论了我们的方法的特点，并评估我们的方法对国家的最先进的方法。
英文摘要：
Creating comprehensible visualizations of highly overlapping set-typed data is a challenging task due to its complexity. To facilitate insights into set connectivity and to leverage semantic relations between intersections, we propose a fast two-step layout technique for Euler diagrams that are both well-matched and well-formed. Our method conforms to established form guidelines for Euler diagrams regarding semantics, aesthetics, and readability. First, we establish an initial ordering of the data, which we then use to incrementally create a planar, connected, and monotone dual graph representation. In the next step, the graph is transformed into a circular layout that maintains the semantics and yields simple Euler diagrams with smooth curves. When the data cannot be represented by simple diagrams, our algorithm always falls back to a solution that is not well-formed but still well-matched, whereas previous methods often fail to produce expected results. We show the usefulness of our method for visualizing set-typed data using examples from text analysis and infographics. Furthermore, we discuss the characteristics of our approach and evaluate our method against state-of-the-art methods.
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。
