Abstract
Information graphics (bar charts, line graphs, grouped bar charts, etc.) often appear in popular media such as newspapers and magazines. In most cases, the information graphic is intended to convey a high-level message; this message plays a role in understanding the document but is seldom repeated in the document’s text. This paper presents our methodology for recognizing the intended message of a grouped bar chart. We discuss the types of messages communicated in grouped bar charts, the communicative signals that serve as evidence for the message, and the design and evaluation of our implemented system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anderson, J.R., Lebiere, C.: The Atomic Components of Thought. Lawrence Erlbaum Associates, Mahwah (1998)
Anderson, J.R., Matessa, M., Lebiere, C.: Act-r: A theory of higher level cognition and its relation to visual attenion. Human-Computer Interaction 12, 439–462 (1997)
Burns, R., Elzer, S., Carberry, S.: Modeling relative task effort for grouped bar charts. In: Taatgen, N., van Rijn, H. (eds.) Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 2292–2297. Cognitive Science Society, Austin (2009)
Carberry, S., Elzer, S., Demir, S.: Information graphics: An untapped resource of digital libraries. In: Proceedings of 9th International ACM SigIR Conference on Research and Development on Information Retrieval, pp. 581–588. ACM, New York (2006)
Chester, D., Elzer, S.: Getting Computers to See Information Graphics So Users Do Not Have to. In: Hacid, M.-S., Murray, N.V., Raś, Z.W., Tsumoto, S. (eds.) ISMIS 2005. LNCS (LNAI), vol. 3488, pp. 660–668. Springer, Heidelberg (2005)
Clark, H.: Using Language. Cambridge University Press (1996)
Elzer, S., Carberry, S., Chester, D., Demir, S., Green, N., Zukerman, I., Trnka, K.: Exploring and exploiting the limited utility of captions in recognizing intention in information graphics. In: Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, pp. 223–230 (2005)
Elzer, S., Carberry, S., Demir, S.: Communicative signals as the key to automated understanding of bar charts. In: Proceedings of the International Conference on the Theory and Application of Diagrams (2006)
Elzer, S., Carberry, S., Zukerman, I., Chester, D., Green, N., Demir, S.: A probabilistic framework for recognizing intention in information graphics. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 223–230. Association for Computational Linguistics, Morristown (2005)
Elzer, S., Green, N., Carberry, S., Hoffman, J.: A model of perceptual task effort for bar charts and its role in recognizing intention. International Journal on User Modeling and User-Adapted Interaction 16, 1–30 (2006)
Fasciano, M., Lapalme, G.: Intentions in the coordinated generation of graphics and text from tabular data. Knowledge and Information Systems 2(3) (August 2000)
Green, N.L., Carenini, G., Kerpedjiev, S., Mattis, J., Moore, J.D., Roth, S.F.: Autobrief: an experimental system for the automatic generation of briefings in integrated text and information graphics. International Journal of Human-Computer Studies 61(1), 32–70 (2004)
Huang, W., Tan, C.L.: A system for understanding imaged infographics and its applications. In: Proceedings of the 2007 ACM Symposium on Document Engineering, DocEng 2007, pp. 9–18. ACM, New York (2007)
Kerpedjiev, S., Green, N., Moore, J., Roth, S.: Saying it in graphics: from intentions to visualizations. In: Proceedings of the Symposium on Information Visualization (InfoVis 1998). IEEE Computer Society Technical Committee on Computer Graphics, pp. 97–101. IEEE (1998)
Larkin, J.H., Simon, H.A.: Why a diagram is (sometimes) worth a thousand words. Cognitive Science 11, 65–99 (1987)
Mittal, V.O., Carenini, G., Moore, J.D., Roth, S.: Describing complex charts in natural language: A caption generation system. Computational Linguistics 24(3), 431–467 (1998)
Peebles, D., Cheng, P.C.H.: Modeling the effect of task and graphical representation on response latency in a graph reading task. Human Factors 45, 28–45 (2003)
Pinker, S.: A theory of graph comprehension. In: Artificial Intelligence and the Future of Testing, pp. 73–126. Lawrence Erlbaum Associates, Hillsdale (1990)
Shah, P., Mayer, R.E., Hegarty, M.: Graphs as aids to knowledge construction: Signaling techniques for guiding the process of graph comprehension. Educational Psychology 91, 690–702 (1999)
Wickens, C.D., Carswell, C.M.: The proximity compatibility principle: Its psychological foundation and relevance to display design. Human Factors 37, 473–494 (1995)
Wu, P., Carberry, S., Elzer, S., Chester, D.: Recognizing the Intended Message of Line Graphs. In: Goel, A.K., Jamnik, M., Narayanan, N.H. (eds.) Diagrams 2010. LNCS, vol. 6170, pp. 220–234. Springer, Heidelberg (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Burns, R., Carberry, S., Elzer, S., Chester, D. (2012). Automatically Recognizing Intended Messages in Grouped Bar Charts. In: Cox, P., Plimmer, B., Rodgers, P. (eds) Diagrammatic Representation and Inference. Diagrams 2012. Lecture Notes in Computer Science(), vol 7352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31223-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-31223-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31222-9
Online ISBN: 978-3-642-31223-6
eBook Packages: Computer ScienceComputer Science (R0)