Der Einsatz von Neural Language Models für eine barrierefreie Verwaltungskommunikation: Anforderungen an die automatisierte Vereinfachung rechtlicher Informationstexte
| dc.contributor.author | Gille, Michael | |
| dc.contributor.author | Schomacker, Thorben | |
| dc.contributor.author | von der Hülls, Jörg | |
| dc.contributor.author | Tropmann-Frick, Marina | |
| dc.contributor.editor | Gunnar Auth | |
| dc.contributor.editor | Tim Pidun | |
| dc.date.accessioned | 2023-11-13T10:19:40Z | |
| dc.date.available | 2023-11-13T10:19:40Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Machine-learning-based text simplification can be used to meet legal obligations to provide comprehensibility-enhanced public service texts. The article examines the use of artificial intelligence for public administration communication in rule-based easy language. The authors outline essential technical, legal and normative requirements for the development and use of automated text simplification through neural language generation. As part of the Open-LS research project, a contribution is made to clarifying the possibilities and limits of the use of artificial intelligence systems for text simplification in public services. | de;en |
| dc.identifier.doi | 10.18420/rvi2023-013 | |
| dc.identifier.isbn | 978-3-88579-735-7 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/42620 | |
| dc.language.iso | de | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | 6. Fachtagung Rechts- und Verwaltungsinformatik (RVI 2023) | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-341 | |
| dc.subject | Text simplification | |
| dc.subject | Transformer | |
| dc.subject | AI Regulation | |
| dc.subject | Leichte Sprache | |
| dc.subject | DIN SPEC 33429 | |
| dc.title | Der Einsatz von Neural Language Models für eine barrierefreie Verwaltungskommunikation: Anforderungen an die automatisierte Vereinfachung rechtlicher Informationstexte | de;en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 158 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 144 | |
| gi.conference.date | 26.-27. October 2023 | |
| gi.conference.location | Dresden | |
| gi.conference.review | full | |
| gi.conference.sessiontitle | Regular Research Papers |
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