Cognitive Computing Recipes 2019
DOI: 10.1007/978-1-4842-4106-6_5
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Cognitive Robotics Process Automation: Automate This!

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Cited by 6 publications
(5 citation statements)
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“…chatbots as process triggers, computer vision to access virtual desktops, data analytics for data hygiene). A number of studies (46%) expand the scope of RPA implementation beyond basic BPI concerns, by mentioning either the knowledge management approach instated by a CoE or the “Intelligent Process Automation” (with cognitive automation ingredients) (Masood and Hashmi, 2019). This mechanism is triggered by expected strategic benefits considering a longer-term knowledge management strategy with a focus on RPA and directly impacts value network outcomes (e.g.…”
Section: Cimo Resultsmentioning
confidence: 99%
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“…chatbots as process triggers, computer vision to access virtual desktops, data analytics for data hygiene). A number of studies (46%) expand the scope of RPA implementation beyond basic BPI concerns, by mentioning either the knowledge management approach instated by a CoE or the “Intelligent Process Automation” (with cognitive automation ingredients) (Masood and Hashmi, 2019). This mechanism is triggered by expected strategic benefits considering a longer-term knowledge management strategy with a focus on RPA and directly impacts value network outcomes (e.g.…”
Section: Cimo Resultsmentioning
confidence: 99%
“…Since 2012, there has been a proliferation of RPA definitions, covering three major aspects: (1) the subject of automationtasks, processes and repetitive tasks (Aguirre and Rodriguez, 2017;Fernandez and Aman, 2018;Kyher€ oinen, 2018;Lewicki et al, 2019;Morrison, 2019;Schmitz et al, 2019a;Theyssens, 2017) ; (2) the nature of automation and its effects-imitating and replacing of human work (Jalonen, 2017;K€ am€ ar€ ainen, 2018;Zhang and Liu, 2018); and (3) the nature of the RPA artefact-a software tool (Aguirre and Rodriguez, 2017;Leno et al, 2018;Morrison, 2019;Ratia et al, 2018;Suri et al, 2018;Theyssens, 2017). Two types of RPA are recognized by both practitioners and researchers: traditional RPA, as the initial form of RPA which is capable to automate processes where structured data and deterministic rules are available, and cognitive or intelligent RPA, as a more recent form of RPA, which grows hand in hand with artificial intelligence (AI) technologies to deal with unstructured data, by learning, reasoning and self-correction (Atroley et al, 2016;Lacity and Willcocks, 2018;Masood and Hashmi, 2019). Although 10 years old, there are wide expectations for rapid adoption of RPA across a wide range of sectors.…”
Section: Introductionmentioning
confidence: 99%
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“…In their survey, Kamran and other researchers analyzed text feature extractions [9], [10], dimentionality reduction methods, existing algorithms and techniques, evaluation methods and limitations [7] and advantages based on applications. Paramesh et al and Seongwook et al compare the different classification algorithms such as multinomial naive bayes logistic regression, K-Nearest neighbour and Support Vector Machines (SVM) on real-world IT infrastructure ticket classifier system data, using different evaluation metrics in their research [11], [12].…”
Section: Related Workmentioning
confidence: 99%
“…Hartmann et al and his team present in their study that RF exhibits high performance in sentiment classification research done on 41 social media data sets covering major social media platforms, where the SVM never outperforms the RF [13]. Cognitive RPA is efficiently undertaken as a low cost solution with Microsoft Azure Language Understanding Intelligent Service (LUIS) [9] and Azure machine learning studio.…”
Section: Related Workmentioning
confidence: 99%