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dc.contributor.authorLensu, Anssi
dc.date.accessioned2008-01-09T12:56:01Z
dc.date.available2008-01-09T12:56:01Z
dc.date.issued2002
dc.identifier.isbn951-39-1355-4
dc.identifier.otheroai:jykdok.linneanet.fi:888141
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/13284
dc.description.abstractThis study focuses on computationally intelligent methods, which are applied to the analysis of survey data in educational research. The methods can be used with complex data sets, which contain several data types. Each data type is analyzed in a separate subanalysis, and the results from these subanalyses can be combined. The methodology makes it possible to locate groups of similar answers from the subanalyses, and to identify these groups using background information. It also allows one to compare groups that are selected from different subanalyses, from different populations, and to locate and identify similar textual answers. In connection to this study, a software application has been created to test the developed methods.en
dc.format.extentverkkoaineisto.
dc.language.isoeng
dc.publisherUniversity of Jyväskylä
dc.relation.ispartofseriesJyväskylä studies in computing
dc.relation.isversionofMyös painettuna.
dc.rightsIn Copyright
dc.titleComputationally intelligent methods for qualitative data analysis
dc.typeDiss.
dc.identifier.urnURN:ISBN:951-39-1355-4
dc.type.dcmitypeTexten
dc.type.ontasotVäitöskirjafi
dc.type.ontasotDoctoral dissertationen
dc.contributor.tiedekuntaInformaatioteknologian tiedekuntafi
dc.contributor.tiedekuntaFaculty of Information Technologyen
dc.contributor.yliopistoUniversity of Jyväskyläen
dc.contributor.yliopistoJyväskylän yliopistofi
dc.contributor.oppiaineTietotekniikkafi
dc.relation.issn1456-5390
dc.relation.numberinseries23
dc.rights.accesslevelopenAccess
dc.subject.ysotietojenkäsittely
dc.subject.ysotiedonlouhinta
dc.subject.ysoneuroverkot
dc.subject.ysokyselytutkimus
dc.rights.urlhttps://rightsstatements.org/page/InC/1.0/


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