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Hauptverfasser: Prucha, Petr, Madzik, Peter, Falat, Lukas
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2404.05836
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author Prucha, Petr
Madzik, Peter
Falat, Lukas
author_facet Prucha, Petr
Madzik, Peter
Falat, Lukas
contents Robotic Process Automation (RPA) has rapidly evolved into a widely recognized and influential software technology. Its growing relevance has sparked diverse research efforts across various disciplines. This study aims to map the scientific landscape of RPA by identifying key thematic areas, tracking their development over time, and assessing their academic impact. To achieve this, we apply an unsupervised machine learning technique Latent Dirichlet Allocation (LDA) to analyze the abstracts of over 2,000 scholarly articles. Our analysis reveals 100 distinct research topics, with 15 of the most prominent themes featured in a science map designed to support future exploration and understanding of RPA's expanding research frontier.
format Preprint
id arxiv_https___arxiv_org_abs_2404_05836
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hiden Topics in Robotic Process Automation -- an Approach based on AI
Prucha, Petr
Madzik, Peter
Falat, Lukas
Computers and Society
Robotic Process Automation (RPA) has rapidly evolved into a widely recognized and influential software technology. Its growing relevance has sparked diverse research efforts across various disciplines. This study aims to map the scientific landscape of RPA by identifying key thematic areas, tracking their development over time, and assessing their academic impact. To achieve this, we apply an unsupervised machine learning technique Latent Dirichlet Allocation (LDA) to analyze the abstracts of over 2,000 scholarly articles. Our analysis reveals 100 distinct research topics, with 15 of the most prominent themes featured in a science map designed to support future exploration and understanding of RPA's expanding research frontier.
title Hiden Topics in Robotic Process Automation -- an Approach based on AI
topic Computers and Society
url https://arxiv.org/abs/2404.05836