Proceedings

A Probabilistic Framework for Recognizing Intention in Information Graphics

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Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1042-1046.

Abstract

This paper extends language understanding and plan inference to information graphics. We identify the kinds of communicative signals that appear in information graphics, describe how we utilize them in a Bayesian network that hypothesizes the graphic’s intended message, and discuss the performance of our implemented system. This work is part of a larger project aimed at making information graphics accessible to individuals with sight impairments.

Stephanie Elzer, Sandra Carberry, Ingrid Zukerman, Daniel Chester, Nancy L. Green, and Seniz Demir. 2005. A Probabilistic Framework for Recognizing Intention in Information Graphics. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05. IJCAI, 1042–1046. https://ijcai.org/proceedings/2005/46
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