Abstract
Experts who narrate their knowledge in case-like form often express significant parts of it in folk arguments ( considerations for and against alternative recommendations where informal judgment is involved. Such arguments do not fit naturally into common frameworks of case-based reasoning. The knowledge they contain may therefore be overlooked despite its value. The paper indicates a mean of helping knowledge acquisition in such circumstances, proposes numerical taxonomy for structuring case bases where folk arguments are included, and shows how these contributions are used, through an example involving both scientific considerations and subjective expert judgment: allocation of frequencies for shortwave broadcasting.
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
Sørmo, F., Cassens, J., Aamodt, A.: Explanation in case-based reasoning–Perspectives and goals. Artificial Intelligence Review 24, 109–143 (2005)
Chesñevar, C., Maguitman, A., Loui, R.P.: Logical models of argument. ACM Computing Surveys 32, 337–383 (2000)
Toulmin, S.E.: The uses of argument (Updated edition 2003). Cambridge University Press, Cambridge (1958)
Silva, L.A.L., Campbell, J.A., Eastaugh, N., Buxton, B.F.: A Case for Numerical Taxonomy in Case-Based Reasoning. In: The 19th Brazilian Symposium on Artificial Intelligence - SBIA 2008, Salvador, Brazil (to appear, 2008)
Bench-Capon, T.J.M., Dunne, P.E.: Argumentation in artificial intelligence. Artificial Intelligence 171, 619–641 (2007)
Ashley, K.D., Rissland, E.L.: Law, learning and representation. Artificial Intelligence 150, 17–58 (2003)
Pennington, N., Hastie, R.: Reasoning in explanation-based decision making. Cognition 49, 123–163 (1993)
Sneath, P.H., Sokal, R.R.: Numerical taxonomy - The principles and practice of numerical classification. W. H. Freeman and Company, San Francisco (1973)
Magne, L., Jones, T. (eds.): Passport to World Band Radio. Lawrence Magne (2003)
Schreiber, A.T.G., Akkermans, H., Anjewierden, A., Hoog, R.d., Shadbolt, N., Velde, W.v.d., Wielinga, B.: Knowledge engineering and management - The Common KADS Methodology. MIT Press, Cambridge (2000)
Silva, L.A.L., Buxton, B.F., Campbell, J.A.: Enhanced Case-Based Reasoning through Use of Argumentation and Numerical Taxonomy. In: The 20th Int. Florida Artificial Intelligence Research Society Conference (FLAIRS-20), Key West, Florida, pp. 423–428. AAAI Press, Menlo Park (2007)
Schank, R.C.: Explanation Patterns: Understanding Mechanically and Creatively. Lawrence Erlbaum Associates, Inc., Mahwah (1986)
Wagenaar, W.A., van Koppen, P.J., Crombag, H.F.M.: Anchored Narratives. The Psychology of Criminal Evidence. St. Martins Press, New York (1993)
Forbus, K.S.H.: Qualitative reasoning. In: Tucker, A.B. (ed.) The Computer Science and Engineering Handbook, Ch. 32, pp. 715–733. CRC Press, Boca Raton (1997)
Bonnefon, J.-F., Fargier, H.: Comparing Sets of Positive and Negative Arguments: Empirical Assessment of Seven Qualitative Rules. In: Brewka, G., Coradeschi, S., Perini, A., Traverso, P. (eds.) 17th European Conference on Artificial Intelligence (ECAI 2006), Riva del Garda, Italy, pp. 16–20. IOS Press, Amsterdam (2006)
Chen, S.-M., Yeh, M.-S., Hsiao, P.-Y.: A comparison of similarity measures of fuzzy values. Fuzzy Sets and Systems 72, 79–89 (1995)
Jain, A.K., Murty, M.N., Flym, P.J.: Data clustering: A review. ACM Computing Surveys 31, 264–323 (1999)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Silva, L.A.L., Campbell, J.A., Buxton, B.F. (2008). Folk Arguments, Numerical Taxonomy and Case-Based Reasoning. In: Althoff, KD., Bergmann, R., Minor, M., Hanft, A. (eds) Advances in Case-Based Reasoning. ECCBR 2008. Lecture Notes in Computer Science(), vol 5239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85502-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-540-85502-6_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85501-9
Online ISBN: 978-3-540-85502-6
eBook Packages: Computer ScienceComputer Science (R0)