A Hybrid Case-Based Reasoner for Footwear
Design

Julie Main and Tharam S. Dillon

Dept of Computer Science and Computer Engineering
La Trobe University, Bundoora 3083, Australia.
Ph: +61 3 9479-2393, Fax: +61 3 9479-3060
and Expert and Intelligent Systems Laboratory,
Applied Computing Research Institute
Email: main@cs.latrobe.edu.au


Abstract. This paper details the way case-based reasoning has been
used to aid footwear designers in creating new designs while maximizing
component reuse. A hybrid system was created which uses an object-oriented 
memory model, neural networks for retrieval and fuzzy feature
vectors to augment the basic case-based reasoning model. One of the
main tasks involved in the design of any case-based system 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 the
components of this footwear design system and how the various elements
join together to create a useful system, in particular, how the use of
fuzzy feature vectors and neural networks can improve the indexing and
retrieval steps in case-based systems.
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