Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
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Handbook for Evaluating Knowledge-Based Systems - Conceptual Framework and Compendium of Methods (Hardcover, 1997 ed.)
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Handbook for Evaluating Knowledge-Based Systems - Conceptual Framework and Compendium of Methods (Hardcover, 1997 ed.)
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Knowledge-based systems are increasingly found in a wide variety of
settings and this handbook has been written to meet a specific need
in their widening use. While there have been many successful
applications of knowledge-based systems, some applications have
failed because they never received the corrective feedback that
evaluation provides for keeping development focused on the users'
needs in their actual working environment. This handbook provides a
conceptual framework and compendium of methods for performing
evaluations of knowledge-based systems during their development.
Its focus is on the users' and subject matter experts' evaluation
of the usefulness of the system, and not on the developers' testing
of the adequacy of the programming code. The handbook permits
evaluators to systematically answer the following kinds of
questions: Does the knowledge-based system meet the users' task
requirements? Is the system easy to use? Is the knowledge base
logically consistent? Does it meet the required level of expertise?
Does the system improve performance? The authors have produced a
handbook that will serve two audiences: a tool that can be used to
create knowledge-based systems (practitioners, developers, and
evaluators) and a framework that will stimulate more research in
the area (academic researchers and students). To accomplish this,
the handbook is built around a conceptual framework that integrates
the different types of evaluations into the system of development
process. The kinds of questions that can be answered, and the
methods available for answering them, will change throughout the
system development life cycle. And throughout this process, one
needs to know what can be done, and what can't. It is this
dichotomy that addresses needs in both the practitioner and
academic research audiences.
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