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.

中文翻译：

---

估计可视化收益的有界措施：理论论述和概念评价

信息论可以用来分析可视化过程的成本效益。但是，当前的利益衡量标准包含一个无限制的术语，既不容易估计，也不容易理解。在这项工作中，我们建议通过将有界术语替换为无界术语来修订现有的成本效益度量。我们研究了一些有界测度，包括詹森-香农（Jenson-Shannon）发散度和作为这项工作一部分制定的新发散度测度。我们描述了提出新的分歧措施的理由。作为比较评估的第一部分，我们使用视觉分析来支持多标准比较，从而将搜索范围缩小到具有更好数学特性的几个选项。