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Indexing and retrieval of cases in a case-based design system

Published online by Cambridge University Press:  27 February 2009

B. Raphael  and
B. Kumar
B. Raphael
Affiliation:
Department of Civil Engineering, University of Strathclyde, Glasgow G4 0NG, Scotland
B. Kumar
Affiliation:
Department of Civil Engineering, University of Strathclyde, Glasgow G4 0NG, Scotland
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Abstract

This paper discusses the issues related to retrieval of cases in a case-based design system. The limitations of the conventional approaches are brought out, and this is followed by a description of a new approach to indexing and retrieval. This approach aims at capturing control knowledge required for retrieval from individual retrieval examples. Since this approach is based on past retrieval examples, we call it RBEX (Retrieval Based on EXamples). The proposed approach is implemented in a prototype system called CADREM. CADREM uses design methods used in solving past design problems to solve new problems. This is closer to the derivational analogy approach rather than the more common transformational analogy. CADREM has been tried in the domain of conceptual structural design of buildings. Sample outputs from CADREM are also included.

Keywords

Artificial IntelligenceCase-Based ReasoningDesignIndexingRetrieval
Type
Articles
Information
AI EDAM , Volume 10 , Issue 1 , January 1996 , pp. 47 - 63
Copyright
Copyright © Cambridge University Press 1996

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References

REFERENCES

Carbonell, J.G. (1986). Derivational analogy: A theory of reconstructive problem solving and expertise acquisition. Machine Learning 2, 371–391.Google Scholar
Chandrasekaran, B. (1990). Design problem solving: a task analysis. AI Magazine 11(4), 59–71.Google Scholar
Hinrichs, T.R. (1989). Strategies for adaptation and recovery in a design problem solver. Proc. Workshop on Case-Based Reasoning (DARPA) (Hammond, K., Ed.), Morgan Kaufmann, San Mateo, California.Google Scholar
Kolodner, J. (1993). Case Based Reasoning. Morgan Kaufmann, San Mateo, California.CrossRefGoogle Scholar
Koton, P. (1988). Reasoning about evidence in causal explanation. Proc. AAAI-88, pp. 256–261, AAAI Press/MIT Press, Cambridge, Massachusetts.Google Scholar
Matthew, P.W., & Bennett, D.F.H. (1990). Economic Long-Span Concrete Floors. British Cement Association, Wexham Springs, Slough.Google Scholar
Raphael, B., Kumar, B., & McLeod, I.A. (1994). Representing design cases based on methods. In Computing in Civil Engineering (Khozeimeh, K., Ed.), pp. 285–292. ASCE, New York.Google Scholar
Schodek, D.L. (1980). Structures. Prentice Hall, Englewood Cliffs, New Jersey.Google Scholar
Sycara, K., & Navinchandra, D. (1992). Retrieval strategies in a case-based design system. In Artificial Intelligence in Engineering Design (Tong, C., & Sriram, D., Eds.), Vol. 2, pp. 145–163. Academic Press, Boston.CrossRefGoogle Scholar