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doi:10.22028/D291-24953
Titel: | Integrated knowledge utilization and evolution for the conservation of corporate know-how |
VerfasserIn: | Kühn, Otto Becker, Volker Lohnse, Georg Neumann, Philipp |
Sprache: | Englisch |
Erscheinungsjahr: | 1994 |
Quelle: | Kaiserslautern ; Saarbrücken : DFKI, 1994 |
Kontrollierte Schlagwörter: | Künstliche Intelligenz |
DDC-Sachgruppe: | 004 Informatik |
Dokumenttyp: | Forschungsbericht (Report zu Forschungsprojekten) |
Abstract: | Insufficient consideration of knowledge evolution is a frequent cause for the failure of knowledge-based systems (KBSs) in industrial practice. Corporate know-how about the design and manufacturing of a particular product is subject to rather rapid changes, and it is hard to specify in advance exactly what information will be requested by various users. Keeping a KBS for the conservation of corporate know-how up-to-date or even enhancing its utility, thus requires the continuous monitoring of its performance, noting deficiencies, and suggestions for improvements. In the current paper, we discuss different ways in which information collected during knowledge utilization can be exploited for system evolution. We present structure-based rule and concept editors which allow for an immediate integration and formalization of new information, even by rather inexperienced users. A prototypical knowledge conservation system for crankshaft design which was developed in cooperation between the DFKI and a German company is used to illustrate and evaluate our approach. |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291-scidok-37306 hdl:20.500.11880/25009 http://dx.doi.org/10.22028/D291-24953 |
Schriftenreihe: | Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x] |
Band: | 94-31 |
Datum des Eintrags: | 30-Jun-2011 |
Fakultät: | SE - Sonstige Einrichtungen |
Fachrichtung: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Dateien zu diesem Datensatz:
Datei | Beschreibung | Größe | Format | |
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RR_94_31.pdf | 178,15 kB | Adobe PDF | Öffnen/Anzeigen |
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