Learning From and Reasoning About Case-based Reasoning Systems

This paper gives a survey about existing case-based reasoning systems and what can be learned from their development and usage. The information gathering for this survey has been carried out by sending two structured questionnaires to developers of case-based reasoning systems. On the basis of 50 answers coming from all over the world we classify and summarise the results concerning the cases acquired and used, the tasks fulfilled, the background knowledge needed and interesting experiences from bringing the systems into use. The information gathered enables us to identify those steps in the CBR cycle [AaPl94] that require further research and development. Finally we give an outlook to the next step currently underway that is directed towards making the collected CBR cases available in a CBR system that is accessible via WWW. By means of this 'meta CBR system' we give the CBR community an opportunity to learn from experience through using the CBR technology for the improvement of our o wn field

Case-Based Reasoning - Survey and Future Directions

This paper surveys the field of case-based reasoning (CBR) -- both in science and in industrial applications. It starts with a short introduction to the essential ideas and concepts CBR is built upon. Then follows a bit of history that is interesting for understanding the development and the current state of the field. Its main part introduces and reviews the most important sub-fields of CBR: theoretical foundations, CBR for document retrieval, product selection, help-desk support, diagnosis, configuration, planning, and design. In the last part, we discuss why the field has developed rather well and will have a promising future, particularly in new areas like self-service and e-commerce applications in the world wide web

Knowledge-based Diagnosis - Survey and Future Directions

Diagnostic expert systems have long been considered an area where eventually a killer application might emerge . Much time has passed since the first prototypes were demonstrated, but we have not yet seen it in the marketplace -- despite many less spectacular success stories. Is the original idea doomed or will the technology finally live up to the expectations? In this paper we survey the state of the art with an emphasis on highlighting specific values of individual methods as well as considering the context of their use. The ultimate goal is to identify conditions and matching methods that will lead to the kind of success that pragmatist customers will find convincing - and then and only then, a real market presence will result