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Use of fuzzy feature vectors and neural networks for case retrieval in case based systems

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3 Author(s)
Main, J. ; Dept. of Comput. Sci. & Comput. Eng., La Trobe Univ., Bundoora, Vic., Australia ; Dillon, Tharam S. ; Khosla, R.

Case-based reasoning is a subset of artificial intelligence and expert systems, and is a powerful mechanism for developing systems that can learn from and adapt past experiences to solve current problems. One of the main tasks involved in the design of case-based systems is determining the features that make up a case and finding a way to index these cases in a case-base for efficient and correct retrieval. This paper looks at how the use of fuzzy feature vectors and neural networks can improve the indexing and retrieval steps in case-based systems

Published in:

Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American

Date of Conference:

19-22 Jun 1996

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