Unveiling Latent Topics in Robotic Process Automation -- an Approach based on Latent Dirichlet Allocation Smart Review

• URL: http://arxiv.org/abs/2404.05836v1
• Date: Mon, 8 Apr 2024 20:03:06 GMT
• Title: Unveiling Latent Topics in Robotic Process Automation -- an Approach based on Latent Dirichlet Allocation Smart Review
• Authors: Petr Prucha, Peter Madzik, Lukas Falat, Hajo A. Reijers,
• Abstract summary: This study aims to create a science map of RPA and its aspects by revealing latent topics related to RPA. By using an unsupervised machine learning method based on Latent Dirichlet Allocation, we were able to analyse over 2000 paper abstracts. Among these, we found 100 distinct study topics, 15 of which have been included in the science map we provide.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Robotic process automation (RPA) is a software technology that in recent years has gained a lot of attention and popularity. By now, research on RPA has spread into multiple research streams. This study aims to create a science map of RPA and its aspects by revealing latent topics related to RPA, their research interest, impact, and time development. We provide a systematic framework that is helpful to develop further research into this technology. By using an unsupervised machine learning method based on Latent Dirichlet Allocation, we were able to analyse over 2000 paper abstracts. Among these, we found 100 distinct study topics, 15 of which have been included in the science map we provide.

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