Multidimensional projection techniques provide graphical representations computed based on instance similarities to enable the analysis of abstract and possibly large data sets. However, when the data set size grows these graphical representations can hardly avoid overlap among markers. To overcome this issue, while some techniques attempt to remove overlap after multidimensional projection, some projection techniques were developed considering non-overlapping constraints. In this work, we present an analysis of four overlap removal techniques and two projection techniques considering non-overlapping. The evaluation was performed according to five metrics that consider structural and similarity relations, and based on the results we provide a guide to use a technique according to the data set and analysis goals.

中文翻译：

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基于多维投影技术避免可视化中标记重叠的方法评估

多维投影技术提供基于实例相似性计算的图形表示，以实现对抽象数据集和可能的大型数据集的分析。然而，当数据集大小增加时，这些图形表示很难避免标记之间的重叠。为了克服这个问题，虽然一些技术试图在多维投影后去除重叠，但考虑到非重叠约束开发了一些投影技术。在这项工作中，我们分析了四种重叠去除技术和两种考虑非重叠的投影技术。评估是根据考虑结构和相似关系的五个指标进行的，并根据结果我们提供了根据数据集和分析目标使用技术的指南。