Home /Research /Robotic Process Mining
OTHER

Robotic Process Mining

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

Year
2022
Citations
16
Access
Open access

Abstract

Abstract User 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.

Keywords

ExecutableComputer scienceProcess (computing)Process miningAutomationPreprocessorTask (project management)GranularityBusiness processEvent (particle physics)

Related papers

Browse all OTHER papers