AAAI Publications, Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence

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Visual and Spatial Factors in a Bayesian Reasoning Framework for the Recognition of Intended Messages in Grouped Bar Charts
Richard Burns, Sandra Carberry, Stephanie Elzer

Last modified: 2010-07-07


The overall goal of our research is the automatic recognition of the intended message of a grouped bar chart. This paper presents our preliminary work on a system that utilizes the communicative signals in a grouped bar chart as evidence in a Bayesian network that hypothesizes the primary message conveyed by the graphic. The paper discusses the kinds of communicative signals present in grouped bar charts and an ACT-R model for computationalizing one important communicative signal, the relative effort involved in performing the perceptual tasks necessary for the recognition. It also describes our Bayesian network and its implementation on a subset of the kinds of messages that can be conveyed by grouped bar charts.


information graphics; intention; Bayesian network; cognitive modeling

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