Information graphics, such as bar charts and line graphs, that appear in popular media generally have a message that they are intended to convey. We have developed a novel plan inference system that uses evidence in the form of communicative signals from the graphic to recognize the graphic designer's intended message. We contend that plan inference research would benefit from examining how each of its evidence sources impacts the system's success. This paper presents such an evidence analysis for the communicative signals that are captured in our plan inference system, and the paper shows how the results of this evidence analysis are informing our research on plan recognition and application systems. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Carberry, S., & Elzer, S. (2007). Exploiting evidence analysis in plan recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4511 LNCS, pp. 7–16). Springer Verlag. https://doi.org/10.1007/978-3-540-73078-1_4
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