Modelling the CBR Life Cycle
Using Description Logics *

Mercedes Gmez-Albarrn, Pedro A. Gonzlez-Calero,
Beln Daz-Agudo and Carlos Fernndez-Conde

Dep. Sistemas Informticos y Programacin
Universidad Complutense de Madrid
28040 Madrid, Spain
email: {albarran, pedro, belend, carlosf}@sip.ucm.es



Abstract. In this paper Description Logics are presented as a suitable
formalism to model the CBR life cycle. We propose a general model
to structure the knowledge needed in a CBR system, where adaptation
knowledge is explicitly represented. Next, the CBR processes are described 
based on this model and the CBR system OoFRA is presented
as an example of our approach.
References

1.	Ashley, K. & Aleven, V., 1993: A logical representation for relevance criteria, in
Topics in CBR (Wess S., Althoff K. & Richter M., eds.), Springer-Verlag.
2.	Borgida, A., 1996: On the Relative Expressiveness of Description Logics and Predicate 
Logics, Artificial Intelligence Journal, vol. 82, no. 1-2, pp. 353-367.
3.	Brachman, R.J., McGuinness, D.L., Patel-Schneider, P.F., Resnick, L. & Borgida,
A., 1991: Living with CLASSIC: When and How to Use a KL-ONE-Like language, 
in Principles of Semantic Networks, Morgan Kaufmann.
4.	Coupey, P., Fouquere, C. & Salotti, 5., 1998: Formalizing Partial Matching and
Similarity in CBR with a Description Logic, Applied Artificial Intelligence, vol.
12, no. 1, pp. 71-112.
5.	Donini, F.M., Lenzerini, M., Nardi, D., & Schaerf, A., 1996: Reasoning in Description 
Logics, in Foundation of Knowledge Representation, CSLI-Publications.
6.	Fernndez-Chamizo, C., Gonzlez-Calero, P., Gmez-Albarrn, M. & Hernndez-Yez, 
L., 1996: Supporting Object Reuse through Case-Based Reasoning,
Procs. EWCBR 96.
7.	Gmez-Albarrn, M., Gonzlez-Calero, P. & Fernndez-Chamizo, C., 1998:
Framework Understanding through Explicit Knowledge Representation, Procs.
IBERAMIA 98.
8.	Heinsohn, J., Kudenko, D., Nebel, B., and Profitlich, H., 1994: An empirical
analysis of terminological representation systems. Artificial Intelligence, vol. 68,
pp. 367-398
9.	Koehler, J., 1994: An Application of Terminological Logics to Case-based Reasoning, 
Procs. KR 94.
10.	Koehler, J., 1996: Planning from Second Principles, Artificial Intelligence, vol.
87, pp. 145-186.
11.	Kolodner, J., 1993: Case-Based Reasoning, Morgan Kaufmann.
12.	Leake, D. B., Kinley, A., & Wilson, D., 1996: Acquiring Case Adaptation Knowledge: 
A Hybrid Approach, Procs. AAAI 96.
13.	Mac Gregor, R., 1991: The evolving technology of classification-based knowledge
representation systems, in Principles of Semantic Networks: Explorations in the
Representation of Knowledge (J. Sowa, ed.), Morgan Kaufmann.
14.	Napoli, A., Lieber, J., & Courien, R., 1996: Classification-Based Problem Solving
in Case-Based Reasoning, Procs. EWCBR 96.
15.	Napoli, A., Lieber, J. & Simon, A., 1997: A Classification-Based Approach to
Case-Based Reasoning, Procs. DL 97.
16.	Plaza, E., 1995: Cases as Terms: A feature term approach to the structured representation 
of cases, Procs. ICCBR 95.
17.	Richter, M., 1995: The knowledge contained in Similarity Measures. Invited 
talk given at ICCBR95. October, 25. http://wwwagr.informatik.uni-kl.de/lsa/CBR/Richtericcbr95remarks.html
18.	Salotti, S. & Ventos, V., 1998: Study and Formalization of a Case-Based Reasoning
System using a Description Logic, in Procs. EWCBR 98.
19.	Salton, G. & McGill, M. J., 1983: Introduction to Modern Information Retrieval,
McGraw-Hill.
20.	Tautz, C., & Althoff, K., 1997: Using Case-Based Reasoning for Reusing Software
Knowledge, Procs. ICCBR 97.
21.	Yen, J., Teh, H.,& Liu X., 1994: Using Description Logics for Software Reuse and
Case-Based Reasoning, Procs. DL 94.
