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Title: Artificial intelligence optimization strategies for invoice management : a preliminary study
Authors: Lima, Rui
Paiva, Sara
Ribeiro, Jorge
Keywords: Artificial intelligence
Computer vision
Machine learning
Natural language processing
Optical character recognition
Robotic process automation
Issue Date: 2021
Publisher: Springer
Citation: Lima, R., Paiva, S., & Ribeiro, J. (2021). Artificial intelligence optimization strategies for invoice management: a preliminary study. In H. Sharma, M. K. Gupta, G. S. Tomar, & W. Lipo (Eds.), Communication and intelligent systems: proceedings of ICCIS 2020, (pp. 223-234). Springer.
Abstract: It is very common for companies to receive invoices (and other semistructured documents) in paper and PDF files and someone has to manually enter that data into a digital structure like a database or comma-separated values (CSV) file. This type of work is very time-consuming (making it expensive) and exhaustive (making it prone to errors). Data entry activities also force high-paying specialized workers to do repetitive tasks or to outsource that work, making it hard to manage the data workflow. There is a need to automate this type of process. In this context, the following paper presents a preliminary study and review of technologies, tools and recent research strategies for invoice management mainly in the scope of robotic process automation tools.
ISBN: 978-981-16-1088-2
ISSN: 2367-3370
Appears in Collections:ESTG - Artigos indexados à WoS/Scopus

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