Abstract
In high school algebra, “word problems” are notoriously difficult. Students who can solve complex equations have trouble analyzing an English sentence to determine the significant variables and relationships. Professional programmers face the same difficulty. The greatest source of errors is the mapping from informal specifications to a formal language. For expert systems, the problem is even worse. Many of them deal with subjects that have never been formalized, such as medical diagnosis, oil well exploration, or automobile registration. In analyzing those subjects, knowledge engineers have no formal theories to guide them. As an aid to formalization, conceptual analysis provides general techniques for analyzing knowledge on any subject. This chapter presents conceptual analysis as a method of analyzing informal knowledge expressed in natural language as a preliminary stage to encoding it in a knowledge representation language. For the examples in this chapter, conceptual graphs are used as the primary knowledge representation language, but the techniques could be applied to any other artificial intelligence (AI) language.
This is a preview of subscription content, log in via an institution to check access.
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
Buzan, T. (1974). Use both sides of your brain. New York: E. P. Dutton.
Geertz, C. (1983). Local knowledge. New York: Basic Books.
Katz, J. J. (1966). The philosophy of language. New York: Harper & Row.
Lenat, D. B., & Guha, R. V. (1990). Building large knowledge bases. Reading,MA: Addison-Wesley.
Marchetti, J. M., & Morris, R. A. (1989). Representing event identity in semantic analysis. Proceedings of the second Florida Artificial Intelligence Research Symposium (pp. 193–196 ). Orlando, FL.
Montague, R. (1973). The proper treatment of quantification in English. In R. Montague, Formal philosophy (pp. 247–270 ). New Haven, CT: Yale University Press.
Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. Cambridge: Cambridge University Press.
Sowa, J. F. (1984). Conceptual structures: Information processing in mind and machine. Reading, MA: Addison-Wesley.
Sowa, J. F. (1989). Knowledge acquisition by teachable systems. In J. P. Martins & E. M. Morgado (Eds.), EPIA 89: Lecture Notes in Artificial Intelligence (pp. 381–396 ). Berlin: Springer-Verlag.
Vendler, Z. (1967). Linguistics in Philosophy. Ithaca, NY: Cornell University Press.
White, A. R. (1975). Conceptual Analysis. In C. J. Bontempo & J. J. Odell (Eds.), The Owl of Minerva (pp. 103–117 ). New York: McGraw-Hill.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1992 Springer-Verlag New York, Inc.
About this chapter
Cite this chapter
Sowa, J.F. (1992). Conceptual Analysis as a Basis for Knowledge Acquisition. In: Hoffman, R.R. (eds) The Psychology of Expertise. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9733-5_5
Download citation
DOI: https://doi.org/10.1007/978-1-4613-9733-5_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4613-9735-9
Online ISBN: 978-1-4613-9733-5
eBook Packages: Springer Book Archive