User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks
This work addresses the problem of improving efficiency for users building decision-theoretic models, but it is incremental as it builds on existing graphical presentation methods.
The paper tackled the laborious task of probability elicitation in Bayesian networks by proposing user interface tools for navigating conditional probability tables and assessing distributions, and a usability study demonstrated their value.
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.