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Document classification in robotic process automation using artificial intelligence : a preliminary literature review

Bibliographic Details
Main Author: Ribeiro, Jorge
Publication Date: 2020
Other Authors: Lima, Rui, Paiva, Sara
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/20.500.11960/2914
Summary: In recent decades, combined with technological evolution, numerous operational activities of companies are supported by information systems. Despite its advantages, countless routine tasks of the organizations are done manually. In recent years, robotic process automation (RPA) has emerged allowing to create automatic processes to deal with routine tasks. One typical feature of these systems is reading documents via optical character recognition (OCR) that are associated with the classification of documents. This paper aims to present a general study on the document classification process using OCR in RPA processes combined with the application of artificial intelligence. It was intended to carry out a survey of the state of the art of tools and approaches for the classification of documents using AI. Conclusions show that despite the challenges associated with the classification and categorization of documents, the applicability of AI techniques shows good results of accuracy to allow a better efficiency in the automation of RPA processes.
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spelling Document classification in robotic process automation using artificial intelligence : a preliminary literature reviewArtificial intelligenceDocument classificationRobotic process automationIn recent decades, combined with technological evolution, numerous operational activities of companies are supported by information systems. Despite its advantages, countless routine tasks of the organizations are done manually. In recent years, robotic process automation (RPA) has emerged allowing to create automatic processes to deal with routine tasks. One typical feature of these systems is reading documents via optical character recognition (OCR) that are associated with the classification of documents. This paper aims to present a general study on the document classification process using OCR in RPA processes combined with the application of artificial intelligence. It was intended to carry out a survey of the state of the art of tools and approaches for the classification of documents using AI. Conclusions show that despite the challenges associated with the classification and categorization of documents, the applicability of AI techniques shows good results of accuracy to allow a better efficiency in the automation of RPA processes.Springer2022-11-29T19:51:13Z2020-01-01T00:00:00Z20202022-10-26T10:28:40Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/20.500.11960/2914eng2367-33892367-337010.1007/978-981-16-1089-9_18metadata only accessinfo:eu-repo/semantics/openAccessRibeiro, JorgeLima, RuiPaiva, Sarareponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-04-11T08:14:13Zoai:repositorio.ipvc.pt:20.500.11960/2914Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T13:29:54.803881Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Document classification in robotic process automation using artificial intelligence : a preliminary literature review
title Document classification in robotic process automation using artificial intelligence : a preliminary literature review
spellingShingle Document classification in robotic process automation using artificial intelligence : a preliminary literature review
Ribeiro, Jorge
Artificial intelligence
Document classification
Robotic process automation
title_short Document classification in robotic process automation using artificial intelligence : a preliminary literature review
title_full Document classification in robotic process automation using artificial intelligence : a preliminary literature review
title_fullStr Document classification in robotic process automation using artificial intelligence : a preliminary literature review
title_full_unstemmed Document classification in robotic process automation using artificial intelligence : a preliminary literature review
title_sort Document classification in robotic process automation using artificial intelligence : a preliminary literature review
author Ribeiro, Jorge
author_facet Ribeiro, Jorge
Lima, Rui
Paiva, Sara
author_role author
author2 Lima, Rui
Paiva, Sara
author2_role author
author
dc.contributor.author.fl_str_mv Ribeiro, Jorge
Lima, Rui
Paiva, Sara
dc.subject.por.fl_str_mv Artificial intelligence
Document classification
Robotic process automation
topic Artificial intelligence
Document classification
Robotic process automation
description In recent decades, combined with technological evolution, numerous operational activities of companies are supported by information systems. Despite its advantages, countless routine tasks of the organizations are done manually. In recent years, robotic process automation (RPA) has emerged allowing to create automatic processes to deal with routine tasks. One typical feature of these systems is reading documents via optical character recognition (OCR) that are associated with the classification of documents. This paper aims to present a general study on the document classification process using OCR in RPA processes combined with the application of artificial intelligence. It was intended to carry out a survey of the state of the art of tools and approaches for the classification of documents using AI. Conclusions show that despite the challenges associated with the classification and categorization of documents, the applicability of AI techniques shows good results of accuracy to allow a better efficiency in the automation of RPA processes.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01T00:00:00Z
2020
2022-11-29T19:51:13Z
2022-10-26T10:28:40Z
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2367-3389
2367-3370
10.1007/978-981-16-1089-9_18
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