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Comparison of Inductive Inference Mechanisms and their Suitability for an Information Model for the Visualization of Uncertainty

Weber, Moritz ; Staudter, Georg ; Anderl, Reiner (2018)
Comparison of Inductive Inference Mechanisms and their Suitability for an Information Model for the Visualization of Uncertainty.
In: Applied Mechanics and Materials, 885
doi: 10.4028/www.scientific.net/AMM.885.147
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Ontologies represent inter-related semantic information. The automated integration of new knowledge helps to detect and reduce data-induced conflicts and model-based uncertainty in ontologies. However, automatic extension of an existing ontology from heterogeneous distributed sources can often lead to incomplete and contradictory entities. In order to resolve these conflicts and to complete entities, inductive inference mechanisms should be applied in addition to the deductive mechanisms already in use. This paper first describes various inductive inference mechanisms and compares these with each other according to pre-defined requirements and other criteria. Finally, the mechanisms� suitability for an information model for the exchange and visualization of uncertainty in load-carrying systems and possible combinations of the individual mechanisms are discussed, also with respect to the necessity of further modifications of these mechanisms.

Typ des Eintrags: Artikel
Erschienen: 2018
Autor(en): Weber, Moritz ; Staudter, Georg ; Anderl, Reiner
Art des Eintrags: Bibliographie
Titel: Comparison of Inductive Inference Mechanisms and their Suitability for an Information Model for the Visualization of Uncertainty
Sprache: Englisch
Publikationsjahr: 2018
Verlag: Trans Tech Publications
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Applied Mechanics and Materials
Jahrgang/Volume einer Zeitschrift: 885
Veranstaltungstitel: Uncertainty in Mechanical Engineering III
DOI: 10.4028/www.scientific.net/AMM.885.147
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Kurzbeschreibung (Abstract):

Ontologies represent inter-related semantic information. The automated integration of new knowledge helps to detect and reduce data-induced conflicts and model-based uncertainty in ontologies. However, automatic extension of an existing ontology from heterogeneous distributed sources can often lead to incomplete and contradictory entities. In order to resolve these conflicts and to complete entities, inductive inference mechanisms should be applied in addition to the deductive mechanisms already in use. This paper first describes various inductive inference mechanisms and compares these with each other according to pre-defined requirements and other criteria. Finally, the mechanisms� suitability for an information model for the exchange and visualization of uncertainty in load-carrying systems and possible combinations of the individual mechanisms are discussed, also with respect to the necessity of further modifications of these mechanisms.

Freie Schlagworte: Uncertainty, OWL, Ontologies, Inductive Reasoning
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Fachgebiet Datenverarbeitung in der Konstruktion (DiK) (ab 01.09.2022 umbenannt in "Product Life Cycle Management")
DFG-Sonderforschungsbereiche (inkl. Transregio)
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 805: Beherrschung von Unsicherheit in lasttragenden Systemen des Maschinenbaus
Hinterlegungsdatum: 23 Nov 2018 07:54
Letzte Änderung: 21 Okt 2021 05:59
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