条件概率表导航的用户界面工具和贝叶斯网络中概率的启发
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks
摘要：
概率的推导是构建决策理论模型中最费力的任务之一，而且迄今为止在决策理论系统中只受到适度的关注。我们提出了一套图形概率模型的用户界面工具，侧重于概率启发的两个方面：（1）通过条件概率表导航和（2）离散概率分布的交互式图形评估。我们提出了两个新的图形视图，帮助导航非常大的条件概率表：CPTree（条件概率树）和SCPT（收缩条件概率表）。基于对人类定量数据图形化呈现的了解，我们为概率轮和条形图提供了几个有用的增强功能，包括不同的图表样式和选项，可以适应用户的偏好和需求。我们提出了一个简单的可用性研究的结果，证明了所提出的工具的价值。
英文摘要：
Elicitation of probabilities is one of the most laborious tasks in building decision-theoretic models, and one that has so far received only moderate attention in decision-theoretic systems. We propose a set of user interface tools for graphical probabilistic models, focusing on two aspects of probability elicitation: (1) navigation through conditional probability tables and (2) interactive graphical assessment of discrete probability distributions. We propose two new graphical views that aid navigation in very large conditional probability tables: the CPTree (Conditional Probability Tree) and the SCPT (shrinkable Conditional Probability Table). Based on what is known about graphical presentation of quantitative data to humans, we offer several useful enhancements to probability wheel and bar graph, including different chart styles and options that can be adapted to user preferences and needs. We present the results of a simple usability study that proves the value of the proposed tools.
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。
