Visualizing and Understanding Diagnoses

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Journal titleCanadian Artificial Intelligence
AbstractDiagnosis of physical systems such as car or aircraft engines is a complex activity. Technicians combine textual manuals with schematics and some analysis of measured data to diagnose and repair engines. Knowledge-based system designers have added heuristics to link text and graphic (hypermedia) representations of manuals to simplify the tasks of the technicians as implemented in JETA [Halasz91]. Knowledge browsers are used by the developers of such systems to structure and input the knowledge base and are also used in a limited capacity to help the domain experts visualize the knowledge and the various possible relations. Such a browser has been implemented to view and edit JETA's knowledge. In RATIONALE, a diagnostic system that reasons by explaining, explanation is used to understand system reasoning [Abu-Hakima90]. This paper argues that although these knowledge-based approaches help in the visualization and understanding of diagnoses in physical systems, they need to be improved and better integrated into an overall diagnostic environment. Some of the many issues that arise in trying to achieve this are discussed in the paper.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number33220
NPARC number8913121
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Record identifier51f0b543-d21c-4c2e-a030-72194ee394da
Record created2009-04-22
Record modified2016-05-09
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