Robotic Process Mining

Author:

Dumas Marlon,Rosa Marcello La,Leno Volodymyr,Polyvyanyy Artem,Maggi Fabrizio Maria

Abstract

AbstractUser interaction logs allow us to analyze the execution of tasks in a business process at a finer level of granularity than event logs extracted from enterprise systems. The fine-grained nature of user interaction logs open up a number of use cases. For example, by analyzing such logs, we can identify best practices for executing a given task in a process, or we can elicit differences in performance between workers or between teams. Furthermore, user interaction logs allow us to discover repetitive and automatable routines that occur during the execution of one or more tasks in a process. Along this line, this chapter introduces a family of techniques, called Robotic Process Mining (RPM), which allow us to discover repetitive routines that can be automated using robotic process automation technology. The chapter presents a structured landscape of concepts and techniques for RPM, including techniques for user interaction log preprocessing, techniques for discovering frequent routines, notions of routine automatability, as well as techniques for synthesizing executable routine specifications for robotic process automation.

Publisher

Springer International Publishing

Reference45 articles.

1. van der Aalst, W.M.P., Bichler, M., Heinzl, A.: Robotic process automation. BISE 60(4), 269–272 (2018)

2. van der Aalst, W.M.P.: Process mining: a 360 degrees overview. In: van der Aalst, W.M.P., Carmona, J. (eds.) Process Mining Handbook. LNBIP, vol. 448, pp. 3–34. Springer, Cham (2022)

3. van der Aalst, W.M.P.: Foundations of process discovery. In: van der Aalst, W.M.P., Carmona, J. (eds.) Process Mining Handbook. LNBIP, vol. 448, pp. 37–75. Springer, Cham (2022)

4. Abedjan, Z., Morcos, J., Ilyas, I.F., Ouzzani, M., Papotti, P., Stonebraker, M.: Dataxformer: a robust transformation discovery system. In 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, 16–20 May 2016, pp. 1134–1145. IEEE Computer Society (2016)

5. Agostinelli, S.: Automated segmentation of user interface logs using trace alignment techniques (extended abstract). In: Di Ciccio, C., Depaire, B., De Weerdt, J., Di Francescomarino, C., Munoz-Gama, J., (eds.) Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020, vol. 2703, CEUR Workshop Proceedings, pp. 13–14. CEUR-WS.org (2020)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fundamental Framework for Task Mining Technology Adoption;Proceedings of the 2023 9th International Conference on Computer Technology Applications;2023-05-10

2. Creating Translucent Event Logs to Improve Process Discovery;Lecture Notes in Business Information Processing;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3