Case-based reasoning (CBR) is one of the most promising recent technologies for building intelligence into computers. This useful introduction to the technology shows what CBR is, why it is important, and how it can be applied to some intriguing real-world problems. The early part of this text outlines the the so-called four "re-'s" of CBR: retrieve, reuse, revise, and retain. Basically, CBR systems match possible solutions to a database of earlier questions, retrieve the answer, and adapt (or revise) it. If appropriate, CBR systems can even save (or retain) these new problems and solutions to its "case-base" for later reuse. For example, if your car does not start, you can use a CBR to match the characteristics of your problem with a database of diagnoses.
The author does a fine job of distinguishing CBR from other artificial intelligence models, such as expert systems (which are rules-based and can be hard to develop because experts don't always get their expertise translated perfectly by programmers) and neural networks (CBR can be more accurate because it can match characteristics and give a reason, while a neural network cannot), and proving that CBR can be faster computationally. He also gives an excellent presentation on how CBR has been used successfully in a surprising range of applications, such as manufacturing, medicine, law, and help desk systems for products, including Web-based applications systems for users. (Help desk applications are a natural fit for CBR technology, but they are not its only use.)
CBR has already enjoyed considerable success without many people knowing about it. (As the author suggests, expert systems, a promising older artificial intelligence [AI] technology, never quite lived up to its initial dazzle.) The author shows that CBR research has already been used to create products. He provides a survey of tools from two continents as well as an extensive bibliography for those experts who want to read more on the subject.
Customer Reviews & Comments
The author gives a comprehensible introduction to the field of Case Base Reasoning (CBR). He starts with an overview to the various techniques and algorithms to be used with CBR and formulates practical criteria when to use them and when not (e.g. adaptation). Very usefull are the differences to other AI approaches and the criteria to check the applicability of these methods. A chapter on CBR software tools reviews a series of available tools and development shells. Practical examples, especially on helpdesk applications show how CBR has been used successfully in projects. All in all the book demystifies CBR and encourages the use of it for building up decision support systems.
