Retrieving adaptable cases

Abstract

The retrieval of a suitable case is of crucial importance to the success of case-based reasoning. A good criterion for judging “case suitability” is how complex a case will be to adapt. However, it has proven difficult to directly calculate this measure of case “adaptability” without incurring the full cost of adaptation. This has led most researchers to exploit semantic similarity as a more tractable (albeit less accurate) answer to the question of case suitability.

This paper describes an approach to case retrieval that allows case adaptability to be accurately measured whilst overcoming the problems which, in the past, led to the adoption of semantic similarity based methods. We argue that our approach benefits from improved retrieval accuracy, flexibility, and greater overall problem solving efficacy. Our methods are implemented in Déjà Vu, a case-based reasoning system for software design, and we use examples from Déjà Vu to demonstrate our ideas.