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eBook Knowledge acquisition for expert systems ePub

by Anna Hart

eBook Knowledge acquisition for expert systems ePub
Author: Anna Hart
Language: English
ISBN: 0070269092
ISBN13: 978-0070269095
Publisher: McGraw-Hill; 1st American ed edition (1986)
Pages: 180
Category: Mathematics
Subcategory: Science
Rating: 4.2
Votes: 270
Formats: docx lrf txt azw
ePub file: 1902 kb
Fb2 file: 1477 kb

Knowledge Acquisition for Expert Systems.

Knowledge Acquisition for Expert Systems.

Knowledge Acquisition. Details (if other): Cancel. Thanks for telling us about the problem. Knowledge Acquisition for Expert Systems.

Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems

Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. It seems that you're in Russian Federation. We have a dedicated site for Russian Federation.

Knowledge acquisition for expert systems is a subclass of any instructional situation whereby knowledge must be externalized from a human expert and transferred to one or more systems. These systems have historically been other people, as in education and training

Knowledge acquisition for expert systems is a subclass of any instructional situation whereby knowledge must be externalized from a human expert and transferred to one or more systems. These systems have historically been other people, as in education and training. However, with the advent of artificial intelligence, the systems are more frequently becoming computers.

oceedings{Hart1988KnowledgeAF, title {Knowledge acquisition for expert systems}, author {Anna Hart} . Important issues need raising before detailed knowledge acquisition can take place for designing expert systems.

oceedings{Hart1988KnowledgeAF, title {Knowledge acquisition for expert systems}, author {Anna Hart}, year {1988} }. Anna Hart. It is futile to try acquiring knowledge and constructing systems unless it is known what it is for. View via Publisher.

Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and frame-based ontologies.

Expert systems (Computer science), Artificial intelligence, Knowledge acquisition (Expert systems). New York : McGraw-Hill. Books for People with Print Disabilities. Internet Archive Books.

Knowledge Engineering for Expert Systems, Chichester: Ellis Horwood. Knowledge acquisition by encoding expert rules versus computer induction from examples: a case study involving soybean pathology International Journal of Man-Machine Studies 12(1) 63–87

Knowledge Engineering for Expert Systems, Chichester: Ellis Horwood. Guida, G and Tasso, C, (Eds), 1989. Topics in Expert System Design: Methodologies and Tools, Amsterdam: Elsevier. Knowledge acquisition by encoding expert rules versus computer induction from examples: a case study involving soybean pathology International Journal of Man-Machine Studies 12(1) 63–87. Recommend this journal. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine.

Essays contained in this volume examine a number of working or prototype expert systems which have been used to tackle various issues, from social security claims to processes used at ICL. show more. Format Paperback 264 pages.

A guide to the critical part of the knowledge-gathering process - eliciting human expertise for machine representation. This book details the process, models and techniques used by professionals actively involved in expert-system development in business and industry. This updated edition places greater emphasis on prototyping, user involvement and the need for rigorous testing and quality control techniques. A section on human issues has also been extended to include the most recent research. Topics covered include a comparison of systems analysis, the role of the knowledge engineer, reasoning and probability theory, fuzziness in reasoning and machine induction amongst others.
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