使用过程挖掘的机器人流程自动化——一项系统文献综述
Robotic Process Automation Using Process Mining $\unicode{x2013}$ A Systematic Literature Review
AI总结：
本文通过系统文献综述，分析了2018年以来32篇论文，评估过程挖掘在识别可自动化流程、支持RPA实施中的作用，指出事件日志预处理等环节仍面临挑战并需进一步研究。
摘要：
过程挖掘（PM）旨在从事件日志中构建过程图，以帮助发现、自动化、改进和监控组织过程。机器人流程自动化（RPA）使用软件机器人执行通常由人类完成的某些任务。通常很难确定要自动化哪些过程和步骤，尤其是在使用RPA时。PM被视为解决这一难题的一种方法。本文旨在评估过程挖掘在加速和改进RPA实施方面的适用性，以及在整个项目生命周期中遇到的挑战。进行了一项系统文献综述，以考察使用PM技术来理解可通过软件机器人实现自动化的现状过程的方法。使用七个数据库来识别关于该主题的论文。从605篇唯一候选论文中筛选出32篇论文，这些论文均发表于2018年之后，并对其进行了分析。该领域的出版物数量稳步增长，尤其是在2022年期间，这表明人们对PM与RPA结合使用的兴趣日益增加。文献主要关注记录在用户与应用程序交互层面发生的事件的方法，以及发现具有可自动化步骤的例程所需的预处理方法。在对这类事件日志进行预处理时面临重要挑战，并且自动化项目的许多生命周期步骤在现有方法中得到的支持较弱，这表明相应的研究领域需要进一步关注。
英文摘要：
Process mining (PM) aims to construct, from event logs, process maps that can help discover, automate, improve, and monitor organizational processes. Robotic process automation (RPA) uses software robots to perform some tasks usually executed by humans. It is usually difficult to determine what processes and steps to automate, especially with RPA. PM is seen as one way to address such difficulty. This paper aims to assess the applicability of process mining in accelerating and improving the implementation of RPA, along with the challenges encountered throughout project lifecycle. A systematic literature review was conducted to examine the approaches where PM techniques were used to understand the as-is processes that can be automated with software robots. Seven databases were used to identify papers on this topic. A total of 32 papers, all published since 2018, were selected from 605 unique candidate papers and then analyzed. There is a steady increase in the number of publications in this domain, especially during the year 2022, which suggests a raising interest in the combined use of PM with RPA. The literature mainly focuses on the methods to record the events that occur at the level of user interactions with the application, and on the preprocessing methods that are needed to discover routines with the steps that can be automated. Important challenges are faced with preprocessing such event logs, and many lifecycle steps of automation projects are weakly supported by existing approaches suggesting corresponding research areas in need of further attention.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
