Knowledge Acquisition for Case-Based Reasoning

Case-Based Reasoning(CBR) is an appealing technique for developing intelligent systems. Building a good CBR system remains still a difficult task. The main problems remaining are the development of suitable case retrieval and adaptation mechanisms for CBR. The major issues are how and when to capture the necessary knowledge for the both. This book proposes a new approach to address the difficulties. The approach facilitates both, the rule acquisition as well as its validation. As a result the knowledge maintenance task of a knowledge engineer is overcome. This approach is effective with respect to both, the development of highly tailored and complex retrieval and adaptation functions for CBR as well as the provision of an intuitive and feasible approach for the expert. The book explains in depth the development of knowledge-based systems for a particular domain using CBR as an example. The experimental evidence discussed in the book promises to allow a significantly more widespread development and practical deployment of CBR systems in a large variety of application domains including medical applications in a more cost-effective way.

Autorentext

Abdus Salam Khan,Assistant professor and consultant,PhD in Computer Science at the University of New South Wales,Australia, 2004. My interest includes areas of Information retrieval, Data base Management,Software Engineering,Artificial Intelligence, in particularly: Knowledge Acquisition Knowledge Management and Applied Case-Based Reasoning.