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dc.contributor.authorEmmenegger, Sandro
dc.contributor.authorHinkelmann, Knut
dc.contributor.authorLaurenzini, Emanuele
dc.contributor.authorThönssen, Barbara
dc.date.accessioned2015-10-05T15:40:54Z
dc.date.available2015-10-05T15:40:54Z
dc.date.issued2013-01-01T00:00:00Z
dc.identifier.urihttp://hdl.handle.net/11654/8939
dc.description.abstractIn the APPRIS project an Early-Warning-System (EWS) is developed applying semantic technologies, namely an enterprise ontology and an inference engine, for the assessment of procurement risks. Our approach allows for analyzing internal resources (e.g. ERP and CRM data) and external sources (e.g. entries in the Commercial Register and newspaper reports) to assess known risks, but also for identifying black swans, which hit enterprises with no warning but potentially large impact. For proof of concept we developed a prototype that allows for integrating data from various information sources, of various information types (structured and unstructured), and information quality (assured facts, news); automatic identification, validation and quantification of risks and aggregation of assessment results on several granularity levels. The motivating scenario is derived from three business project partners real requirements for an EWS.
dc.language.isoen_UK
dc.publisherSpringer
dc.relation.ispartofFred, Ana
dc.relation.ispartofDietz, Jan L.G
dc.relation.ispartofLiu, Kecheng
dc.relation.ispartofFelipe, Joaquim
dc.relation.ispartofFred, Ana
dc.relation.ispartofDietz, Jan L.G
dc.relation.ispartofLiu, Kecheng
dc.relation.ispartofFelipe, Joaquim
dc.relation.ispartofseriesKnowledge Discovery, Knowledge Engineering and Knowledge Management (Communications in Computer and Information Science)
dc.accessRightsAnonymous
dc.subject.ddc330 - Wirtschaft
dc.subject.ddc005 - Computer Programmierung, Programme und Daten
dc.titleTowards a Procedure for Assessing Supply Chain Risks Using Semantic Technology.
dc.type03 - Sammelband
dc.spatialBerlin
dc.audienceWissenschaft
fhnw.publicationStateVeröffentlicht
fhnw.ReviewTypeKein Peer Review
fhnw.InventedHereunbekannt


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