Abstract
Information graphics (such as bar charts and line graphs) are widely used in popular media. The majority of such non-pictorial graphics have the purpose of communicating a high-level message which is often not repeated in the text of the article. Thus, information graphics together with the textual segments contribute to the overall purpose of an article and cannot be ignored. Unfortunately, information graphics often do not label the dependent axis with a full descriptor of what is being measured. In order to realize the high-level message of an information graphic in natural language, a referring expression for the dependent axis must be generated. This task is complex in that the required referring expression often must be constructed by extracting and melding pieces of information from the textual content of the graphic. Our heuristic-based solution to this problem has been shown to produce reasonable text for simple bar charts. This paper presents the extensibility of that approach to other kinds of graphics, in particular to grouped bar charts and line graphs. We discuss the set of component texts contained in these two kinds of graphics, how the methodology for simple bar charts can be extended to these kinds, and the evaluation of the enhanced approach.
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Demir, S., Elzer Schwartz, S., Burns, R., Carberry, S. (2013). What is being Measured in an Information Graphic?. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2013. Lecture Notes in Computer Science, vol 7816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37247-6_40
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DOI: https://doi.org/10.1007/978-3-642-37247-6_40
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