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Graph-grammar assistance for knowledge acquisition
Abstract One of the most difficult aspects of model One of the most difficult aspects of modeling complex medical dilemmas in decision-analytic terms is composing a diagram of relevance relations from a set of domain concepts. The concepts, as presented to the knowledge engineer, generally have no inherent order, yet they have charcteristic positions and typical roles in a semantic network model. We have been using a graph-grammar production system to express such inherent interrelationships among medical terms. We have found that this graph-grammar system facilitates the modeling of medical dilemmas. We also suggest a translate-and-assemble perspective for certain knowledge-acquisition problems. We suspect that graph grammars,and the translate-and-assemble perspective, may be useful guides to modeling in many other circumscribed domains. eling in many other circumscribed domains.
Address Stanford, CA, USA +
Author John W. Egar +
Bibtype techreport  +
Institution Knowledge Systems, AI Laboratory +
Key KSL-92-37  +
Modification dateThis property is a special property in this wiki. 1 May 2009 13:37:05  +
Month April +
Number KSL-92-37  +
Tag Computer science +
Title Graph-Grammar Assistance for Knowledge Acquisition  +
Tr id KSL-92-37  +
Year 1992  +
Categories Technical Report, Publication, KSL Technical Report
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