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The Knowledge Acquisition Bottleneck: Time for Reassessment?
Author(s) -
Cullen J.,
Bryman A.
Publication year - 1988
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.1988.tb00065.x
Subject(s) - knowledge acquisition , computer science , bottleneck , domain knowledge , domain (mathematical analysis) , matching (statistics) , sample (material) , subject matter expert , expert system , data acquisition , constraint (computer aided design) , knowledge based systems , artificial intelligence , data science , mechanical engineering , mathematical analysis , statistics , chemistry , mathematics , chromatography , engineering , embedded system , operating system
Knowledge acquisition has long been considered to be the major constraint in the development of expert systems. Conventional wisdom also maintains that the major problem encountered in knowledge acquisition is in identifying the varying structures and characteristics of domain knowledge and matching these to suitable acquisition techniques. With the aid of the first substantial systematic analysis of a sample of expert systems applications developed in the real world, the authors describe what is actually going on in terms of knowledge acquisition. In the light of the evidence, it is argued that a reappraisal of the conventional approach to knowledge acquisition is necessary.