Large Language Model-Powered Question-Answering Assistant for Citizen Developers

dc.contributor.authorLuke, Lavina
dc.contributor.mentorMartin, Andreas
dc.contributor.mentorPande, Charuta
dc.date.accessioned2024-12-03T19:23:39Z
dc.date.available2024-12-03T19:23:39Z
dc.date.issued2023
dc.description.abstractThe study explores using Large Language Model-powered QA-assistant to improve Citizen Developers' low-code platform development, addressing uncertainties and expectations surrounding generative AI. The primary objective of this thesis is to answer the main research question of how an LLM-powered QA-Assistant can improve the development process for Citizen developers in a data-centric, low-code platform.
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/48846
dc.language.isoen
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialOlten
dc.subject.ddc330 - Wirtschaft
dc.titleLarge Language Model-Powered Question-Answering Assistant for Citizen Developers
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.StudentsWorkTypeMaster
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutMaster of Science
relation.isMentorOfPublication6a3865e7-85dc-41b5-afe3-c834c56fab4e
relation.isMentorOfPublication6fa75258-21bd-4090-98cb-b2217a6f234d
relation.isMentorOfPublication.latestForDiscovery6a3865e7-85dc-41b5-afe3-c834c56fab4e
Dateien
Sammlung
Master of Science