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Process factors in knowledge acquisition
Author(s) -
Holsapple Clyde W.,
Wagner William P.
Publication year - 1996
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.1468-0394.1996.tb00283.x
Subject(s) - computer science , process (computing) , structuring , bottleneck , knowledge acquisition , representation (politics) , scheme (mathematics) , artificial intelligence , natural language processing , data science , law , economics , embedded system , operating system , mathematical analysis , mathematics , finance , politics , political science
Knowledge acquisition (KA) is often characterised as a crucial bottleneck in the development of expert system applications. General definitions of KA view it as a collection of subprocesses such as elicitation, analysis and representation, but in actual practice, each KA occurrence may involve one or all of these subprocesses in varying sequences and combinations. No model or framework currently exists for describing the many possible variations in KA processes as they actually occur. This article presents a new way of characterising knowledge acquisition processes that is not tied to one particular technique or approach to KA. Three nested levels are proposed to characterise the many possible variations and combinations of KA dynamics: the process, episode and transaction levels of analysis. Each of these is further delineated in a top‐down manner. Not only does this scheme provide a fairly comprehensive means for viewing KA dynamics as a whole, but it suggests several factors that have heretofore drawn little research attention. The suggested constructs capture more accurately what actually occurs in the practice of KA. In so doing they also provide the foundation for structuring future research into how KA processes may unfold.