User Adaptive Inference in Expert Systems

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dc.contributor.authorLee, Jae Kyu-
dc.contributor.authorKwon, Suhn B.-
dc.date.accessioned2013-03-15T00:49:12Z-
dc.date.available2013-03-15T00:49:12Z-
dc.date.created2012-02-06-
dc.date.issued1991-01-
dc.identifier.citationProceedings of Twenty-Fourth Annual Hawaii International Conference on System Sciences, v., no., pp.208 - 217-
dc.identifier.urihttp://hdl.handle.net/10203/115158-
dc.description.abstractDialogues generated by the backward chaining control strategy is not adaptive to the user level. To overcome such a limitation, the authors propose the Question & Adapt (Q&A) approach. The Q&A approach generates dialogue at the user level regardless of the depth of the knowledge base. An issue is how to set and/or adjust user level so as to minimize the expected number of questions. They have developed several theorems and estimators about the average, variance and randomness of user levels. Such findings are applied to the design of user adaptive expert systems.-
dc.languageENG-
dc.titleUser Adaptive Inference in Expert Systems-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.beginningpage208-
dc.citation.endingpage217-
dc.citation.publicationnameProceedings of Twenty-Fourth Annual Hawaii International Conference on System Sciences-
dc.identifier.conferencecountryUnited States-
dc.identifier.conferencecountryUnited States-
dc.contributor.localauthorLee, Jae Kyu-
dc.contributor.nonIdAuthorKwon, Suhn B.-
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MT-Conference Papers(학술회의논문)
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