Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11960/2907
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. https://doi.org/10.1007/978-981-16-1089-9_19 |
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. |
URI: | http://hdl.handle.net/20.500.11960/2907 |
ISBN: | 978-981-16-1088-2 978-981-16-1089-9 |
ISSN: | 2367-3370 |
Appears in Collections: | ESTG - Artigos indexados à WoS/Scopus |
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