Robotic Process Automation in Public Administrations
| dc.contributor.author | Houy, Constantin | |
| dc.contributor.author | Hamberg, Maarten | |
| dc.contributor.author | Fettke, Peter | |
| dc.contributor.editor | Räckers, Michael | |
| dc.contributor.editor | Halsbenning, Sebastian | |
| dc.contributor.editor | Rätz, Detlef | |
| dc.contributor.editor | Richter, David | |
| dc.contributor.editor | Schweighofer, Erich | |
| dc.date.accessioned | 2019-02-22T12:37:10Z | |
| dc.date.available | 2019-02-22T12:37:10Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Against the background of current activities towards administrative modernization based on the digitalization of processes, the usage and integration of Robotic Process Automation (RPA) software into public administration work processes can significantly improve their efficiency, reduce process costs and provide better services for citizens. This paper presents and investigates the concept of RPA and discusses the particular potential and challenges of RPA in the public administration context. Furthermore, it demonstrates an application example of a new cognitive RPA approach for automated data extraction and processing that is used in a trade tax assessment scenario using deep convolutional neural networks (CNN). Based on the findings it can be concluded that RPA has considerable potential for the improvement of the efficiency of administrative work processes and for administrative modernization in general. | en |
| dc.identifier.isbn | 978-3-88579-685-5 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/20517 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Digitalisierung von Staat und Verwaltung | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-291 | |
| dc.subject | Robotic Process Automation | |
| dc.subject | RPA | |
| dc.subject | Cognitive RPA | |
| dc.subject | Business Process Management | |
| dc.subject | BPM | |
| dc.subject | Deep Learning | |
| dc.subject | Convolutional Neural Networks | |
| dc.title | Robotic Process Automation in Public Administrations | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 74 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 62 | |
| gi.conference.date | 6.-7. März 2019 | |
| gi.conference.location | Münster |
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