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Enterprise Knowledge Modeling, UML vs Ontology: Formal Evaluation

2019

International audience; Everyday activities in enterprises rely heavily on the experts' know-how. Due to experts departure, the loss of expertise and knowledge is a reoccurring problem in these enterprises. Recently, in order to capture experts knowledge into intelligent systems, formal knowledge representation methods, such as ontologies, are being studied and have caught up with non-formal or semi-formal representation, such as UML. The similarities and differences between UML class diagram and computational ontology have for long raised questions about the possibility of synthesizing them in a common representation (usually an ontology). Indeed, the problem of migrating knowledge encoded…

REPRESENTATIONKnowledge representation and reasoningComputer sciencebusiness.industryIntelligent decision support system02 engineering and technologyOntology (information science)computer.software_genre[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Knowledge modelingUnified Modeling LanguageCode refactoring020204 information systemsSIMILARITY0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]020201 artificial intelligence & image processingClass diagramSoftware engineeringbusinesscomputercomputer.programming_languageSemantic matching2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)
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