Enhancing non-expert understanding of Artificial Intelligence solutions through an ontology-based approach

dc.contributor.authorCastratori, Sarah Graziella
dc.contributor.mentorLaurenzi, Emanuele
dc.date.accessioned2024-12-03T19:39:14Z
dc.date.available2024-12-03T19:39:14Z
dc.date.issued2024
dc.description.abstractTo drive AI understanding and adoption, the vast terms, concepts, and definitions around the many different dimensions and aspects of AI must be demystified for a broader non-tech-focused audience. Such as professionals with higher education who work in a digitalized business environment but have no education in computer science or similar fields. These in this context, called “non-experts” of AI, who are decision-makers and contributors in various industries, could profit from an easy, manageable, and trustworthy way to level up their own knowledge of the AI field. Specifically in the context of relevant business challenges and terms.
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/49263
dc.language.isoen
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialOlten
dc.subject.ddc330 - Wirtschaft
dc.titleEnhancing non-expert understanding of Artificial Intelligence solutions through an ontology-based approach
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.StudentsWorkTypeMaster
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutMaster of Science
relation.isMentorOfPublication4a2b6cad-6ed6-4355-a377-e408a177b079
relation.isMentorOfPublication.latestForDiscovery4a2b6cad-6ed6-4355-a377-e408a177b079
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