It seems self-evident that knowledge management and knowledge engineering should share techniques, methods and underlying theory. Yet many in the field of knowledge management are sceptical of this claim, arguing that knowledge engineering often fails to capture the broad context in which knowledge exists. This book presents a multi-perspective modelling approach to representation of knowledge and its context that provides an underlying theory; resolves common issues in ontology development; and guides knowledge engineers ...
Read More
It seems self-evident that knowledge management and knowledge engineering should share techniques, methods and underlying theory. Yet many in the field of knowledge management are sceptical of this claim, arguing that knowledge engineering often fails to capture the broad context in which knowledge exists. This book presents a multi-perspective modelling approach to representation of knowledge and its context that provides an underlying theory; resolves common issues in ontology development; and guides knowledge engineers through system development from organisational modelling to design specification. It includes extensive guidance on developing models using the CommonKADS methodology; on knowledge acquisition; and on selecting AI programming techniques. The guidance is illustrated with artificial intelligence applications including manufacturing and medical diagnosis; mortgage application assessment; search and rescue planning; and air campaign planning. This book constitutes the Ph.D. thesis (by research publications) of John K.C. Kingston, formerly of the Artificial Intelligence Applications Institute at the University of Edinburgh, now a Senior Lecturer in Information Systems and Business Computing at the University of Brighton. John has been described as one of the few people who can make CommonKADS comprehensible.
Read Less
