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dc.contributor.authorSchulze, Sonja
dc.contributor.editorMaier, Ronald
dc.date.accessioned2019-01-17T10:30:21Z
dc.date.available2019-01-17T10:30:21Z
dc.date.issued2011
dc.identifier.isbn978-3-88579-276-5
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/19551
dc.description.abstractThis paper proposes a framework for experience-based decision support by analyzing the use and meaning of experiences in the business context. Two weak points in traditional approaches for reusing experiences e.g. CBR are addressed: First, the lack of adaptability to dynamic business situations and second the lack of analysis capabilities. Therefore, the use of decision support systems that help solving problems by reusing and analyzing experiences with business intelligence methods is proposed. In order to transfer the experiences into computable data a solution adequacy index is calculated that aggregates the single experiences to represent the compiled experience for a specific solution. The whole framework is illustrated by using the example of optimal supplier choice, finally applying two online analytical processing methods out of the BI domain to illustrate the solution adequacy index (SAI).en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof6th Conference on Professional Knowledge Management – From Knowledge to Action
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-182
dc.subjectExperience Management
dc.subjectDecision Support Systems (DSS)
dc.subjectBusiness Intelligence (BI)
dc.subjectOnline Analytical Processing (OLAP)
dc.titleTechniques for reusing experiences (T-REx) in managerial decision-making processesen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages403-406
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationInnsbruck, Austria
mci.conference.dateFebruary 21-23, 2011


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