This paper presents a method for connotatively weighting information presented in graphic displays. The method involves determining a compatibility (unction that describes the degree of correspondence between an implied attribute of the display and the linguistic category that summarizes values of this attribute. Compatibility functions can then be used to guide the graph-construction process.
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References
1.
Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice-Hall.
2.
Kandel, A., and Byatt, W. J. (1978). Fuzzy sets, fuzzy algebra, and fuzzy statistics. Proceedings of the IEEE, 66, 1619–1639.
3.
Kosslyn, S. M., Pinker, S., Parkin, L. P., and Simcox, W. A. (1983, January). Understanding charts and graphs: A Project in applied cognitive science (Report No. NIE 400-79-0066). Washington, DC: National Institute of Education.
4.
Miller, G. A. (1956). The magical number 7 ± 2: Some limits on our capacity for processing information. Psychological Review, 1956, 63(2), 81–97.
5.
Rosch, E. (1978). Principles of categorization. In E, Rosch and B. Lloyd (Eds.), Cognition and categorization. Hillsdale, NJ: Erlbaum.
6.
Rouse, W, B. (1980). Systems engineering models of human-machine illustration. New York: North Holland.
7.
Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8, 338–353.
8.
Zadeh, L. A. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man, and Cybernecics, 3(1), 28–44.
9.
Zadeh, L. A., Fu, K. S., Tanaka, K., and Shimura, M. (Eds.) (1975). Fuzzy sets and their applications to cognitive and decision processes. New York: Academic Press.
