Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11960/2907
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DC Field | Value | Language |
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dc.contributor.author | Lima, Rui | - |
dc.contributor.author | Paiva, Sara | - |
dc.contributor.author | Ribeiro, Jorge | - |
dc.date.accessioned | 2022-11-29T16:45:02Z | - |
dc.date.available | 2022-11-29T16:45:02Z | - |
dc.date.issued | 2021 | - |
dc.identifier.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 | pt_PT |
dc.identifier.isbn | 978-981-16-1088-2 | - |
dc.identifier.isbn | 978-981-16-1089-9 | - |
dc.identifier.issn | 2367-3370 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11960/2907 | - |
dc.description.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. | pt_PT |
dc.language.iso | eng | pt_PT |
dc.publisher | Springer | - |
dc.rights | closedAccess | pt_PT |
dc.subject | Artificial intelligence | pt_PT |
dc.subject | Computer vision | pt_PT |
dc.subject | Machine learning | pt_PT |
dc.subject | Natural language processing | pt_PT |
dc.subject | Optical character recognition | pt_PT |
dc.subject | Robotic process automation | pt_PT |
dc.title | Artificial intelligence optimization strategies for invoice management : a preliminary study | pt_PT |
dc.type | conferenceObject | pt_PT |
dc.date.updated | 2022-10-26T10:29:13Z | - |
dc.description.version | 5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira Paiva | - |
dc.description.version | N/A | - |
dc.identifier.slug | cv-prod-3062415 | - |
degois.publication.firstPage | 223 | pt_PT |
degois.publication.lastPage | 234 | pt_PT |
degois.publication.volume | 204 | pt_PT |
degois.publication.title | Communication and intelligent systems: proceedings of ICCIS 2020 | pt_PT |
dc.identifier.doi | 10.1007/978-981-16-1089-9_19 | - |
dc.identifier.eid | 2-s2.0-85111985895 | - |
Appears in Collections: | ESTG - Artigos indexados à WoS/Scopus |
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File | Description | Size | Format | |
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2021_24.pdf Restricted Access | 287.35 kB | Adobe PDF | View/Open Request a copy |
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