Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11960/2907
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dc.contributor.authorLima, Rui-
dc.contributor.authorPaiva, Sara-
dc.contributor.authorRibeiro, Jorge-
dc.date.accessioned2022-11-29T16:45:02Z-
dc.date.available2022-11-29T16:45:02Z-
dc.date.issued2021-
dc.identifier.citationLima, 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_19pt_PT
dc.identifier.isbn978-981-16-1088-2-
dc.identifier.isbn978-981-16-1089-9-
dc.identifier.issn2367-3370-
dc.identifier.urihttp://hdl.handle.net/20.500.11960/2907-
dc.description.abstractIt 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.isoengpt_PT
dc.publisherSpringer-
dc.rightsclosedAccesspt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectComputer visionpt_PT
dc.subjectMachine learningpt_PT
dc.subjectNatural language processingpt_PT
dc.subjectOptical character recognitionpt_PT
dc.subjectRobotic process automationpt_PT
dc.titleArtificial intelligence optimization strategies for invoice management : a preliminary studypt_PT
dc.typeconferenceObjectpt_PT
dc.date.updated2022-10-26T10:29:13Z-
dc.description.version5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira Paiva-
dc.description.versionN/A-
dc.identifier.slugcv-prod-3062415-
degois.publication.firstPage223pt_PT
degois.publication.lastPage234pt_PT
degois.publication.volume204pt_PT
degois.publication.titleCommunication and intelligent systems: proceedings of ICCIS 2020pt_PT
dc.identifier.doi10.1007/978-981-16-1089-9_19-
dc.identifier.eid2-s2.0-85111985895-
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