Extraction of information from invoices - challenges in the extraction pipeline

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Extraction of information from invoices - challenges in the extraction pipeline. / Thiée, Lukas Walter; Krieger, Felix; Funk, Burkhardt.
INFORMATIK 2023: Designing Futures: Zukünfte gestalten, 26. – 29. September 2023, Berlin. Hrsg. / Maike Klein; Daniel Krupka; Cornelia Winter; Volker Wohlgemuth. Bonn: Gesellschaft für Informatik e.V., 2023. S. 1777-1792 (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings; Band P-337).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

Thiée, LW, Krieger, F & Funk, B 2023, Extraction of information from invoices - challenges in the extraction pipeline. in M Klein, D Krupka, C Winter & V Wohlgemuth (Hrsg.), INFORMATIK 2023: Designing Futures: Zukünfte gestalten, 26. – 29. September 2023, Berlin. GI-Edition: Lecture Notes in Informatics (LNI), Proceedings, Bd. P-337, Gesellschaft für Informatik e.V., Bonn, S. 1777-1792, 53. Jahrestagung der Gesellschaft für Informatik e.V.(GI) - INFORMATIK 2023, Berlin, Berlin, Deutschland, 26.09.23. https://doi.org/10.18420/inf2023_180

APA

Thiée, L. W., Krieger, F., & Funk, B. (2023). Extraction of information from invoices - challenges in the extraction pipeline. In M. Klein, D. Krupka, C. Winter, & V. Wohlgemuth (Hrsg.), INFORMATIK 2023: Designing Futures: Zukünfte gestalten, 26. – 29. September 2023, Berlin (S. 1777-1792). (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings; Band P-337). Gesellschaft für Informatik e.V.. https://doi.org/10.18420/inf2023_180

Vancouver

Thiée LW, Krieger F, Funk B. Extraction of information from invoices - challenges in the extraction pipeline. in Klein M, Krupka D, Winter C, Wohlgemuth V, Hrsg., INFORMATIK 2023: Designing Futures: Zukünfte gestalten, 26. – 29. September 2023, Berlin. Bonn: Gesellschaft für Informatik e.V. 2023. S. 1777-1792. (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings). doi: 10.18420/inf2023_180

Bibtex

@inbook{91e4805e665944859a408ddaa0389860,
title = "Extraction of information from invoices - challenges in the extraction pipeline",
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.",
keywords = "Data pipeline., Information extraction, Invoice recognition, Informatics, Business informatics",
author = "Thi{\'e}e, {Lukas Walter} and Felix Krieger and Burkhardt Funk",
note = "Publisher Copyright: {\textcopyright} 2023 Gesellschaft fur Informatik (GI). All rights reserved.; 53. Annual Meeting of the German Informatics Society (GI) - INFORMATICS 2023, INFORMATICS 2023 ; Conference date: 26-09-2023 Through 29-09-2023",
year = "2023",
doi = "10.18420/inf2023_180",
language = "English",
series = "GI-Edition: Lecture Notes in Informatics (LNI), Proceedings",
publisher = "Gesellschaft f{\"u}r Informatik e.V.",
pages = "1777--1792",
editor = "Maike Klein and Daniel Krupka and Cornelia Winter and Volker Wohlgemuth",
booktitle = "INFORMATIK 2023",
address = "Germany",
url = "https://informatik2023.gi.de/",

}

RIS

TY - CHAP

T1 - Extraction of information from invoices - challenges in the extraction pipeline

AU - Thiée, Lukas Walter

AU - Krieger, Felix

AU - Funk, Burkhardt

N1 - Conference code: 53

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Data pipeline.

KW - Information extraction

KW - Invoice recognition

KW - Informatics

KW - Business informatics

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U2 - 10.18420/inf2023_180

DO - 10.18420/inf2023_180

M3 - Article in conference proceedings

AN - SCOPUS:85181143950

T3 - GI-Edition: Lecture Notes in Informatics (LNI), Proceedings

SP - 1777

EP - 1792

BT - INFORMATIK 2023

A2 - Klein, Maike

A2 - Krupka, Daniel

A2 - Winter, Cornelia

A2 - Wohlgemuth, Volker

PB - Gesellschaft für Informatik e.V.

CY - Bonn

T2 - 53. Annual Meeting of the German Informatics Society (GI) - INFORMATICS 2023

Y2 - 26 September 2023 through 29 September 2023

ER -

DOI