Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/132725
DC FieldValue
dc.titleModelling human cognition in problem diagnosis: A hybrid case-based reasoning methodology
dc.contributor.authorLaw, Y.F.D.
dc.date.accessioned2016-12-13T05:35:48Z
dc.date.available2016-12-13T05:35:48Z
dc.date.issued1997-06
dc.identifier.citationLaw, Y.F.D. (1997-06). Modelling human cognition in problem diagnosis: A hybrid case-based reasoning methodology. Informatica (Ljubljana) 21 (2) : 209-217. ScholarBank@NUS Repository.
dc.identifier.issn03505596
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/132725
dc.description.abstractAs modern business functions become more knowledge-intensive, the demand for intelligent and knowledge-based systems has increased. Part of the challenge of developing quality expert systems lies in the effective modelling of cognitive processes of human experts and representation of various forms of related knowledge in a domain. This paper describes a cognitive-driven methodology for the development of expert systems based on a hybrid reasoning approach. The methodology incorporates a hybrid case-based reasoning (CBR) framework of techniques which include case memory organisation networks, case indexing and retrieval schemes; and an interactive and incremental style of reasoning. The paper will discuss the design and implementation of an expert system in a problem response help desk environment of a local bank, as an example of a successful application of this methodology.
dc.sourceScopus
dc.subjectCognitive processes
dc.subjectFault diagnosis
dc.subjectHelp desk
dc.subjectHybrid case-based reasoning
dc.typeArticle
dc.contributor.departmentCTR FOR MGT OF INNO. & TECHNOPRENEURSHIP
dc.description.sourcetitleInformatica (Ljubljana)
dc.description.volume21
dc.description.issue2
dc.description.page209-217
dc.description.codenINFOF
dc.identifier.isiutNOT_IN_WOS
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