Extraction of Information from Invoices – Challenges in the Extraction Pipeline
| dc.contributor.author | Thiée, Lukas-Walter | |
| dc.contributor.author | Krieger, Felix | |
| dc.contributor.author | Funk, Burkhardt | |
| dc.contributor.editor | Klein, Maike | |
| dc.contributor.editor | Krupka, Daniel | |
| dc.contributor.editor | Winter, Cornelia | |
| dc.contributor.editor | Wohlgemuth, Volker | |
| dc.date.accessioned | 2023-11-29T14:50:23Z | |
| dc.date.available | 2023-11-29T14:50:23Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Data from invoices are key information for business processes. In order to use the data and create business value, the information must be captured in a digital and structured form. Leveraging digital tools and AI/ML is state-of-the-art in the extraction of information from invoices. However, the existing approaches are trained on specific languages and layouts, and while focusing on the performance of individual metrics, they neglect the demonstration of the pipeline from raw data to processable information. In this paper, we investigate the types of information on invoices and address the challenges in the extraction pipeline. We contribute by providing a morphological framework for the problematization and design of a pipeline as part of a design science study. | en |
| dc.identifier.doi | 10.18420/inf2023_180 | |
| dc.identifier.isbn | 978-3-88579-731-9 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/43108 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | INFORMATIK 2023 - Designing Futures: Zukünfte gestalten | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-337 | |
| dc.subject | Invoice recognition | |
| dc.subject | Information extraction | |
| dc.subject | Data pipeline | |
| dc.title | Extraction of Information from Invoices – Challenges in the Extraction Pipeline | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 1792 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 1777 | |
| gi.conference.date | 26.-29. September 2023 | |
| gi.conference.location | Berlin | |
| gi.conference.sessiontitle | Wirtschaft, Management Industrie - Joint Workshop IntDig 2023 MOC 2023; Intelligente Digitalisierung, (KI-basiertes) Management und Optimierung komplexer Systeme |
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