一种有界的可视化效益评估方法：理论话语与概念评估
A Bounded Measure for Estimating the Benefit of Visualization: Theoretical Discourse and Conceptual Evaluation
摘要：
信息论可用于分析可视化过程的成本效益。然而，目前衡量效益的标准包含一个不受限制的术语，既不容易估计，也不容易直观地解释。在这项工作中，我们建议修改现有的成本效益措施，取代无界的一个有界的。我们研究了一些有界的措施，包括詹森-香农分歧和一个新的分歧措施制定这项工作的一部分。我们描述了提出一个新的分歧措施的理由。作为比较评估的第一部分，我们使用可视化分析来支持多标准比较，将搜索范围缩小到具有更好数学属性的几个选项。本文的理论论述和概念评价为通过综合和实验案例研究进行进一步的比较评价提供了基础，这些案例将在单独的论文中报告。
英文摘要：
Information theory can be used to analyze the cost-benefit of visualization processes. However, the current measure of benefit contains an unbounded term that is neither easy to estimate nor intuitive to interpret. In this work, we propose to revise the existing cost-benefit measure by replacing the unbounded term with a bounded one. We examine a number of bounded measures that include the Jenson-Shannon divergence and a new divergence measure formulated as part of this work. We describe the rationale for proposing a new divergence measure. As the first part of comparative evaluation, we use visual analysis to support the multi-criteria comparison, narrowing the search down to several options with better mathematical properties. The theoretical discourse and conceptual evaluation in this paper provide the basis for further comparative evaluation through synthetic and experimental case studies, which are to be reported in a separate paper.
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。
