Vis enkel innførsel

dc.contributor.advisorAamodt, Agnarnb_NO
dc.contributor.advisorFaxvaag, Arildnb_NO
dc.contributor.authorMarthinsen, Tor Henrik Aasnessnb_NO
dc.date.accessioned2014-12-19T13:31:57Z
dc.date.available2014-12-19T13:31:57Z
dc.date.created2010-09-03nb_NO
dc.date.issued2007nb_NO
dc.identifier347540nb_NO
dc.identifierntnudaim:1374nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/250556
dc.description.abstractIn this thesis we describe our study of two knowledge intensive Conversational Case-Based Reasoning (CCBR) systems and their methods. We look in particular at the way they have solved inferencing and question ranking. Then we continue with a description of our own design for a CCBR system, that will help patients share their experiences of side effects with drugs, with other patients. We describe how we create cases, how our question selection methods work and present an example of how the domain model will look. It is also included a simulation of how a dialogue would be for a patient. The design we have created is a good basis for implementing a knowledge intensive CCBR system. The system should work better than a normal CCBR system, because of the inferencing and question ranking methods, which should lessen the cognitive load on the user and require fewer questions answered, to reach a good solution.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaimno_NO
dc.subjectSIF2 datateknikkno_NO
dc.subjectIntelligente systemerno_NO
dc.titleConversational CBR for Improved Patient Information Acquisitionnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber53nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


Tilhørende fil(er)

Thumbnail
Thumbnail
Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel