一种基于聚集的可视化整体质量度量方法
An Aggregation-Based Overall Quality Measurement for Visualization
摘要：
美学常被用来评价图形绘制的质量。然而，现有的美学标准是有用的，在判断的程度，一个图形符合特定的绘图规则。他们在评价整体质量方面有局限性。目前，图形绘制的整体质量主要基于个人判断和用户研究来评估。个人判断是不可靠的，而用户研究可能是昂贵的运行。因此，有必要直接衡量整体质量。可视化设计人员可以使用此度量在设计阶段快速比较手头的图形质量并做出相应的决策。为了满足这一需求，我们提出了一种基于个人审美标准聚合来衡量整体质量的措施。我们提出了一项用户研究，验证了这一措施，并证明了它预测人类图形理解性能的能力。建议的措施，为未来的研究的影响进行了讨论。
英文摘要：
Aesthetics are often used to evaluate the quality of graph drawings. However, the existing aesthetic criteria are useful in judging the extents to which a drawing conforms to particular drawing rules. They have limitations in evaluating overall quality. Currently the overall quality of graph drawings is mainly evaluated based on personal judgments and user studies. Personal judgments are not reliable, while user studies can be costly to run. Therefore, there is a need for a direct measure of overall quality. This measure can be used by visualization designers to quickly compare the quality of drawings at hand at the design stage and make decisions accordingly. In an attempt to meet this need, we propose a measure that measures overall quality based on aggregation of individual aesthetic criteria. We present a user study that validates this measure and demonstrates its capacity in predicting the performance of human graph comprehension. The implications of the proposed measure for future research are discussed.
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