Authoring case based training by document data extraction

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dc.creatorBetz, Christian
dc.creatorHoernlein, Alexander
dc.creatorPuppe, Frank
dc.date2005-09-14
dc.date.accessioned2026-07-07T03:23:26Z
dc.date.available2026-07-07T03:23:26Z
dc.descriptionIn this paper, we propose an scalable approach to modeling based upon word processing documents, and we describe the tool Phoenix providing the technical infrastructure. For our training environment d3web.Train, we developed a tool to extract case knowledge from existing documents, usually dismissal records, extending Phoenix to d3web.CaseImporter. Independent authors used this tool to develop training systems, observing a significant decrease of time for setteling-in and a decrease of time necessary for developing a case.
dc.description11 pages, 10th ChEM Workshop, 2005; technical article
dc.identifierhttps://arxiv.org/abs/cs/0509040
dc.identifierhttp://arxiv.org/abs/cs/0509040
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32943
dc.subjectArtificial Intelligence
dc.subjectInformation Retrieval
dc.titleAuthoring case based training by document data extraction
dc.typetext

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