The visual display of quantitative information
The visual display of quantitative information
Interactive graphic design using automatic presentation knowledge
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using argumentation to control lexical choice: a functional unification implementation
Using argumentation to control lexical choice: a functional unification implementation
Integrating planning and task-based design for multimedia presentation
Proceedings of the 2nd international conference on Intelligent user interfaces
Semiology of graphics
How to Lie With Statistics
An interactive visualization method of numerical data based on natural language requirements
International Journal of Human-Computer Studies - Special issue on HCI research in Japan
International Journal of Human-Computer Studies
Answering it with charts: dialogue in natural language and charts
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Extending plan inference techniques to recognize intentions in information graphics
UM'03 Proceedings of the 9th international conference on User modeling
The automated understanding of simple bar charts
Artificial Intelligence
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Graphical presentations can be very effective in communicating large datasets and patterns, trends and relationships in them. Charts and graphs used in reporting data usually tend to highlight certain aspects and suppress others. In fact, a recent study of several hundred annual reports found that more than 30% of charts in these reports were designed to facilitate inferences favorable to the companies while hindering others. Unfortunately, many of the techniques used to achieve these effects may not be obvious to the average user. One solution to this problem is to make design choices explicit to the user. This paper presents a data analysis interface that educates users by enabling them to explore the visualization space and modifying chart design parameters. This interface is based on an analysis of a corpus of charts and graphs and uses knowledge about a variety of techniques for emphasizing specific trends and/or values shown in 2-D charts and graphs.