Knowledge Engineering Methodology: An Annotated Bibliography of NEOMYCIN Research

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Citation: William J. Clancey. (1988) Knowledge Engineering Methodology: An Annotated Bibliography of NEOMYCIN Research. In KSL-87-58, 1988.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author William J. Clancey
title Knowledge Engineering Methodology: An Annotated Bibliography of NEOMYCIN Research
number KSL-87-58
institution Knowledge Systems, AI Laboratory
year 1988
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publisher Springer-Verlag
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abstract From a broad perspective, knowledge engineering is a methodology for acquiring, representing, and using qualitative models of systems. We distinguish between systems being modeled (physical, cognitive, social, ect.), modeling tasks (such as diagnosis and control), computational methods (such as heuristic classification), and implementation languages (such as rules and frames). The pragmatic value of this perspective is illustrated by uncovering knowledge representation problems in existing expert systems. New languages make explicit the dimensions of task system model, computational method, and implementation. In state-of-the-art expert system shells, the representation of reasoning strategy is emphasized, illustrated here with examples of enhanced explanation, student modeling, and knowledge acquisition. Beyond this, we consider philosophical limitations of the representational approach and implications for future research.

KSL Technical Report ID: KSL-87-58
Facts about Knowledge Engineering Methodology: An Annotated Bibliography of NEOMYCIN ResearchRDF feed
Abstract From a broad perspective, knowledge engine … From a broad perspective, knowledge engineering is a methodology for acquiring, representing, and using qualitative models of systems. We distinguish between systems being modeled (physical, cognitive, social, ect.), modeling tasks (such as diagnosis and control), computational methods (such as heuristic classification), and implementation languages (such as rules and frames). The pragmatic value of this perspective is illustrated by uncovering knowledge representation problems in existing expert systems. New languages make explicit the dimensions of task system model, computational method, and implementation. In state-of-the-art expert system shells, the representation of reasoning strategy is emphasized, illustrated here with examples of enhanced explanation, student modeling, and knowledge acquisition. Beyond this, we consider philosophical limitations of the representational approach and implications for future research. oach and implications for future research.
Author William J. Clancey  +
Bibtype techreport  +
Has author William J. Clancey  +
Has identifier KSL-87-58  +
Has publishing details 1988  +
Has title Knowledge Engineering Methodology: An Annotated Bibliography of NEOMYCIN Research  +
Has where published KSL-87-58  +
Has year 1988  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-87-58  +
Number KSL-87-58  +
Process note GOOGLE  +
Publisher Springer-Verlag  +
Title Knowledge Engineering Methodology: An Annotated Bibliography of NEOMYCIN Research  +
Year 1988  +
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