Visual and spatial factors in a Bayesian reasoning framework for the recognition of intended messages in grouped bar charts
Richard J. Burns, Sandra Carberry, Stephanie Elzer · 2010
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 asubsetofthekindsofmessagesthatcanbeconveyedby grouped bar charts.