{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:46:16Z","timestamp":1742913976202,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":44,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811610882"},{"type":"electronic","value":"9789811610899"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-1089-9_18","type":"book-chapter","created":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T18:04:04Z","timestamp":1624903444000},"page":"211-221","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Document Classification in Robotic Process Automation Using Artificial Intelligence\u2014A Preliminary Literature Review"],"prefix":"10.1007","author":[{"given":"Jorge","family":"Ribeiro","sequence":"first","affiliation":[]},{"given":"Rui","family":"Lima","sequence":"additional","affiliation":[]},{"given":"Sara","family":"Paiva","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,29]]},"reference":[{"key":"18_CR1","unstructured":"Under the hood of AI document classification. https:\/\/www.bizdata.com.au\/blogpost.php?p=under-the-hood-of-ai-document-classification. Last accessed 2020\/09\/11"},{"key":"18_CR2","unstructured":"Automatic machine learning document classification\u2014an introduction. https:\/\/provalisresearch.com\/blog\/automatic-machine-learning-document-classification\/. Last accessed 2020\/09\/11"},{"key":"18_CR3","unstructured":"Problem-solving with ML: automatic document classification. AI & Machine Learning. https:\/\/cloud.google.com\/blog\/products\/gcp\/problem-solving-with-ml-automatic-document-classification. Last accessed 2020\/09\/11"},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"Aalst W, Bichler M, Heinzl A (2018) Robotic process automation. Bus Inf Syst Eng 60","DOI":"10.1007\/s12599-018-0542-4"},{"key":"18_CR5","doi-asserted-by":"publisher","first-page":"100007","DOI":"10.1016\/j.fsir.2019.100007","volume":"1","author":"A Asquith","year":"2019","unstructured":"Asquith A, Horsman G (2019) Let the robots do it!\u2014taking a look at robotic process automation and its potential application in digital forensics. Forensic Sci Int Rep 1:100007","journal-title":"Forensic Sci Int Rep"},{"key":"18_CR6","doi-asserted-by":"crossref","unstructured":"Enr\u00edquez JG, Jim\u00e9nez-Ram\u00edrez A, Dom\u00ednguez-Mayo FJ, Garc\u00eda-Garc\u00eda JA (2020) Robotic process automation: a scientific and industrial systematic mapping study. IEEE Access 8:39113\u201339129","DOI":"10.1109\/ACCESS.2020.2974934"},{"key":"18_CR7","unstructured":"Williams D, Allen I (2017) Using artificial intelligence to optimize the value of robotic process automation"},{"key":"18_CR8","doi-asserted-by":"crossref","unstructured":"Anagnoste S (2017) Robotic automation process\u2014the next major revolution in terms of back office operations improvement. In: Proceedings of the international conference on business excellence 11","DOI":"10.1515\/picbe-2017-0072"},{"key":"18_CR9","doi-asserted-by":"crossref","unstructured":"William W, William L (2019) Improving corporate secretary productivity using robotic process automation. In: International conference on technologies and applications of artificial intelligence, pp 1\u20135","DOI":"10.1109\/TAAI48200.2019.8959872"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Syed R, Suriadi S, Adams M, Bandara W el al (2020) Robotic process automation: contemporary themes and challenges. Comput Ind 115","DOI":"10.1016\/j.compind.2019.103162"},{"key":"18_CR11","first-page":"235","volume":"82","author":"C Kaya","year":"2019","unstructured":"Kaya C, Turkyilmaz M, Birol B (2019) Impact of RPA technologies on accounting systems. J Acc Financ 82:235\u2013249","journal-title":"J Acc Financ"},{"key":"18_CR12","doi-asserted-by":"publisher","first-page":"39113","DOI":"10.1109\/ACCESS.2020.2974934","volume":"8","author":"JG Enriquez","year":"2020","unstructured":"Enriquez JG, Jimenez-Ramirez A, Dominguez-Mayo FJ, Garcia-Garcia JA (2020) Robotic process automation: a scientific and industrial systematic mapping study. IEEE Access 8:39113\u201339129","journal-title":"IEEE Access"},{"key":"18_CR13","unstructured":"Lima R (2018) Extra\u00e7\u00e3o e an\u00e1lise multidimensional de dados de atletismo a partir de dados n\u00e3o estruturados (Master\u2019s thesis), Mestrado em Engenharia de Software, Instituto Polit\u00e9cnico de Viana do Castelo"},{"issue":"11","key":"18_CR14","first-page":"414","volume":"7","author":"R Talib","year":"2016","unstructured":"Talib R, Hanif MK, Ayesha S, Fatima F (2016) Text mining: techniques, applications and issues. Int J Adv Comput Sci Appl 7(11):414\u2013418","journal-title":"Int J Adv Comput Sci Appl"},{"key":"18_CR15","unstructured":"Text analysis, classification and categorization. https:\/\/monkeylearn.com\/text-analysis\/. Last accessed 2020\/09\/11"},{"key":"18_CR16","unstructured":"AI Document Classification Process. https:\/\/www.parascript.com\/blog\/leveraging-ai-in-document-classification\/. Last accessed 2020\/09\/11"},{"key":"18_CR17","unstructured":"Artificial intelligence RPA capabilities. https:\/\/www.uipath.com\/product\/ai-rpa-capabilities. Last accessed 2020\/09\/11"},{"key":"18_CR18","unstructured":"Kofax intelligent automation platform. https:\/\/www.kofax.com\/Products\/intelligent-automation-platform. Last accessed 2020\/09\/11"},{"key":"18_CR19","unstructured":"IQBot\u2014Intelligent document processing. https:\/\/www.automationanywhere.com\/products\/iq-bot. Last accessed 2020\/09\/11"},{"key":"18_CR20","unstructured":"About Softomotive. https:\/\/www.winautomation.com\/about-softomotive\/. Last accessed 2020\/09\/11"},{"key":"18_CR21","unstructured":"IBM RPA. https:\/\/www.ibm.com\/products\/robotic-process-automation. Last accessed 2020\/09\/11"},{"key":"18_CR22","unstructured":"TagUI\u2014AI Singapore platform\u2014National Institute. https:\/\/makerspace.aisingapore.org\/do-ai\/tagui\/. Last accessed 2020\/09\/11"},{"key":"18_CR23","unstructured":"RPA. https:\/\/www.edgeverve.com\/assistedge\/robotic-process-automation\/. Last accessed 2020\/09\/11"},{"key":"18_CR24","unstructured":"Automagica GitHub repository. https:\/\/github.com\/automagica\/automagica. Last accessed 2020\/09\/11"},{"key":"18_CR25","unstructured":"Robocorp hub. https:\/\/hub.robocorp.com\/new-to-robocorp-suite\/get-started\/quickstart-guide\/. Last accessed 2020\/09\/11"},{"key":"18_CR26","unstructured":"TaskT RPA .NET platform. https:\/\/github.com\/saucepleez\/taskt\/wiki\/Automation-Commands. Last accessed 2020\/09\/11"},{"key":"18_CR27","doi-asserted-by":"publisher","first-page":"263","DOI":"10.2478\/v10177-011-0035-6","volume":"57","author":"A Bilski","year":"2011","unstructured":"Bilski A (2011) A review of artificial intelligence algorithms in document classification. Int J Electron Telecommun 57:263\u2013270","journal-title":"Int J Electron Telecommun"},{"key":"18_CR28","unstructured":"Chakravarthy T, Arivoli P (2015) Document classification using machine learning algorithms\u2014a review. Int J Sci Eng Res (IJSER) 2347\u20133878"},{"key":"18_CR29","doi-asserted-by":"crossref","unstructured":"Thangaraj M, Sivakami M (2018) Text classification techniques: a literature review","DOI":"10.28945\/4066"},{"key":"18_CR30","doi-asserted-by":"crossref","unstructured":"Tripathi K, Vyas R, Gupta A (2019) Document classification using artificial neural networks. Research Gate Publication","DOI":"10.51983\/ajcst-2019.8.2.2140"},{"key":"18_CR31","doi-asserted-by":"publisher","first-page":"437","DOI":"10.14419\/ijet.v7i4.34.26907","volume":"7","author":"W Noormanshah","year":"2018","unstructured":"Noormanshah W, Nohuddin P, Zainol Z (2018) Document categorization using decision tree: preliminary study. Int J Eng Technol 7:437\u2013440","journal-title":"Int J Eng Technol"},{"key":"18_CR32","first-page":"117","volume":"13","author":"M Thangaraj","year":"2018","unstructured":"Thangaraj M, Sivakami M (2018) Text classification techniques: a literature review. Interdiscip J Inf Knowl Manag 13:117\u2013135","journal-title":"Interdiscip J Inf Knowl Manag"},{"key":"18_CR33","unstructured":"Sivakumar R, Manikandan R (2018) Machine learning algorithms for text-documents classification: a review. Int J Acad Res Dev. ISSN: 2455-4197"},{"key":"18_CR34","unstructured":"Anderlucci L, Guastadisegni L, Viroli C (2019) Classifying textual data: shallow, deep and ensemble methods"},{"key":"18_CR35","unstructured":"UIPath\u2014Element recognition in user visual interface. https:\/\/www.uipath.com\/product\/platform\/ai-computer-vision-for-rpa. Last accessed 2020\/09\/11"},{"issue":"2\u20133","key":"18_CR36","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/S0921-8890(02)00355-X","volume":"43","author":"J Fritsch","year":"2003","unstructured":"Fritsch J, Kleinehagenbrock M et al (2003) Multi-modal anchoring for human\u2013robot interaction. Robot Auton Syst 43(2\u20133):133\u2013147","journal-title":"Robot Auton Syst"},{"key":"18_CR37","unstructured":"Kofax\u2014Cognitive document automation. https:\/\/www.kofax.com\/Blog\/Categories\/Cognitive-Document-Automation. Last accessed 2020\/09\/11"},{"key":"18_CR38","unstructured":"Google Tensorflow. https:\/\/www.tensorflow.org\/. Last accessed 2020\/09\/11"},{"key":"18_CR39","unstructured":"Automation anywhere\u2014Artificial neural networks. https:\/\/www.automationanywhere.com\/images\/Datasheet_IQ_Bot.pdf. Last accessed 2020\/09\/11"},{"key":"18_CR40","unstructured":"AssistEdge\u2014Use of artificial neural networks to analyze business process variations. https:\/\/www.edgeverve.com\/assistedge\/assistedge-discover\/. Last accessed 2020\/09\/11"},{"key":"18_CR41","unstructured":"Natural Processing Language usage. https:\/\/makerspace.aisingapore.org\/do-ai\/hotdocs-nlp. Last accessed 2020\/09\/11"},{"key":"18_CR42","unstructured":"Microsoft Text Analytics API [Online]. https:\/\/docs.microsoft.com\/en-us\/azure\/cognitive-services\/text-analytics\/. Last accessed 2020\/09\/11"},{"key":"18_CR43","unstructured":"Google Natural Language API. https:\/\/cloud.google.com\/natural-language\/docs\/languages. Last accessed 2020\/09\/11"},{"key":"18_CR44","unstructured":"Microsoft Azure machine learning algorithm cheat sheet. https:\/\/docs.microsoft.com\/pt-pt\/azure\/machine-learning\/algorithm-cheat-sheet. 2020\/09\/11"}],"container-title":["Lecture Notes in Networks and Systems","Communication and Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-1089-9_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T20:39:46Z","timestamp":1672605586000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-1089-9_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811610882","9789811610899"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-1089-9_18","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"29 June 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}