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dc.contributor.advisorAamodt, Agnarnb_NO
dc.contributor.authorBakke, Elisenb_NO
dc.date.accessioned2014-12-19T13:32:56Z
dc.date.available2014-12-19T13:32:56Z
dc.date.created2010-09-03nb_NO
dc.date.issued2005nb_NO
dc.identifier348054nb_NO
dc.identifierntnudaim:991nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/250910
dc.description.abstractThis thesis contains a study of state of the art knowledge acquisition modelling principles and methods for modelling general domain knowledge. This includes Newell's knowledge level, knowledge level modelling, Components of Expertise, CommonKADS and the Protégé meta tool. The thesis also includes a short introduction to the knowledge-intensive case-based reasoning system TrollCreek. Based on this background knowledge, one did analysis and comparison of different possible solutions. Then, after justifying the choices made, a knowledge acquisition method for TrollCreek was created. The method was illustrated through an example, evaluated and discussed.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaimno_NO
dc.subjectSIF2 datateknikkno_NO
dc.subjectProgram- og informasjonssystemerno_NO
dc.titleKnowledge acquisition and modelling for knowledge-intensive CBRnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber114nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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