Abstract
A major goal of this paper is to compare Case Based Reasoning with other methods searching for knowledge. We consider knowledge as a resource that can be traded. It has no value in itself; the value is measured by the usefulness of applying it in some process. Such a process has info-needs that have to be satisfied. The concept to measure this is the economical term utility. In general, utility depends on the user and its context, i.e., it is subjective. Here we introduce levels of context from general to individual. We illustrate that Case Based Reasoning on the lower, i.e., more personal levels CBR is quite useful, in particular in comparison with traditional informational retrieval methods.
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References
Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications 7, 39–59 (1994)
Althoff, K.-D., Althoff, B., Althoff, B.A., von Wangenheim, C.G., Tautz, C.: CBR for Experimental Software Engineering. Case-Based Reasoning Technology, 235–254 (1998)
Althoff, K.-D., Weber, R.O.: Knowledge Management in Case-Based Reasoning. Knowledge Engineering Review 20(3), 305–310 (2005)
Ardito, R., Bara, B.G., Blanzieri, E.: A cognitive Account of Situated Communication COGSCI 2002 (2002)
Bello-Tomás, J.J., González-Calero, P.A., Díaz-Agudo, B.: JColibri: an Object-Oriented Framework for Building CBR Systems. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, Springer, Heidelberg (2004)
Bergmann, R., Richter, M.M., Schmitt, S., Stahl, A., Vollrath, I.: Utility-Oriented Matching: A New Research Direction for Case-Based Reasoning. In: Vollrath, I., Schmitt, S., Reimer, U. (eds.) Proc. of the 9th German Workshop on Case-Based Reasoning, GWCBR 2001, Baden-Baden, Germany, Baden-Baden, Germany. In: Schnurr, H.-P., Staab, S., Studer, R., Stumme, G., Sure, Y (Hrsg.): Professionelles Wissensmanagement. Shaker Verlag (2001)
Brüninghaus, S., Ashley, K.: The Role of Information Extraction in Textual CBR. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS (LNAI) (SNLAI), vol. 2080, pp. 74–80. Springer, Heidelberg (2001)
CBR-Works (2003), sern.ucalgary.ca/courses/SENG/609.13/W2004/06.%20CBR-Works.pdf
Holz, H.: Process-Based Knowledge Management Support for Software Engineering, Doctoral Dissertation University of Kaiserslautern, disserertations.de Online-Press (2002)
Jacobson, A., Prusak, L.: The Cost of Knowledge. Harvard Business Review (2007)
jcolibri (2002), http://gaia.fdi.ucm.es/projects/jcolibri
von Neumann, J., Morgenstern, O.: Theory of Games and Behavior, 1953th edn. Princeton University Press, Princeton, NJ (1944)
orenge:dialog. In: orenge: Open Retrieval Engine 3.2 Manual. empolis – knowledge management, http://www.km.empolis.com/
Richter, M.M.: Terminology in Complex Domains. In: Bock, H., Polasek, W. (eds.) Proc. Of the 19th Annual Conference of the Gesellschaft für Klassifikation. Studies in Classification, Data Analysis and Knowledge Organization, pp. 416–426. Springer, Heidelberg (1995)
Richter, M.M.: Introduction. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI) (SNLAI), vol. 1400, Springer, Heidelberg (1998)
Richter, M.M.: Foundations of Similarity and Utility. In: Proc. FLAIRS 2007, AAAI Press, Stanford, California (2007)
Richter, M.M.: Similarity. In: Perner, P. (ed.) Case-Based Reasoning on Signals and Images, Springer, Heidelberg
Riloff, E.: Automatically Extraction Information Patterns from Untagged Text. In: Proc.of the 13th National Conference on Artificial Intelligence, AAAI Press, Stanford, California (1996)
Savage, J.L.: 1954. Foundations of Statistics. Reprint: Dover Publications; 2d Rev. ed. (1972)
Schmitt, S., Bergmann, F.R.: A formal approach to dialogs with online customers. In: 14th Bled Electronic Commerce Conference (2001)
Schmitt, S., Dopichaj, P., Domínguez-Marín, P.: Entropy-based vs. Similarity-influenced: Attribute Selection Methods for Dialogs Tested on Different Electronic Commerce Domains. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, Springer, Heidelberg (2002)
Stahl, A.: Learning of Knowledge-Intensive Similarity Measures in Case-Based Reasoning. Kaiserslautern (2003)
Weber, R., Aha, D.W., Becerra-Fernandez, I.: Intelligent Lessons Learned Systems. Expert Systems with Applications 20(1), 17–34 (2001)
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Richter, M.M. (2007). Case Based Reasoning and the Search for Knowledge. In: Perner, P. (eds) Advances in Data Mining. Theoretical Aspects and Applications. ICDM 2007. Lecture Notes in Computer Science(), vol 4597. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73435-2_1
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DOI: https://doi.org/10.1007/978-3-540-73435-2_1
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