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.

翻译：信息理论可以用来分析可视化过程的成本效益。然而,目前的效益计量方法包含一个既难于估计、又不易理解的不受约束的术语。在这项工作中,我们提议修订现有的成本效益计量方法,用一个受约束的术语取代无约束术语。我们研究了一些约束性措施,其中包括延森-沙农差异和作为这项工作一部分而拟订的新的差异计量方法。我们描述了提出新的差异计量方法的理由。作为比较评估的第一部分,我们利用视觉分析来支持多标准比较,将搜索范围缩小到几个具有较好数学属性的选项。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一步进行比较评估提供了基础,这些研究将在一份单独的文件中报告。