House calls : building and maintaining a rule-base

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Journal titleKnowledge Acquisition
Pages379402; # of pages: 24
AbstractA knowledge-acquisition system was designed and built to help an architectural firm automate their diagnosis of building problems. The system was tailored to the firm's database system and building survey method. Rules are generated from the data by the induction learning algorithms ID3 or AQll and the orderly development of the rule-base is ensured by a verification procedure. Architectural diagnostics rely on the expertise of an experienced analyst. Building diagnostic processes require spatial, verbal and numerical reasoning. The rigid data structure imposed by the firm excluded crucial levels of semantic information. Induction methods proved useful tools for organizing data, but the expertise was captured by ad hac editing of the rule-base. This project identified a need in the building industry to develop a taxonomy and a representation to support the building diagnostic process.
Publication date
AffiliationNRC Institute for Research in Construction; National Research Council Canada
Peer reviewedYes
NRC number36005
NPARC number20375199
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Record identifier69755865-90ae-49c0-822a-556f35493f0d
Record created2012-07-23
Record modified2016-05-09
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