Title
Identifying Candidate Routines for Robotic Process Automation from Unsegmented UI Logs
Abstract
Robotic Process Automation (RPA) is a technology to develop software bots that automate repetitive sequences of interactions between users and software applications (a.k. a. routines). To take full advantage of this technology, organizations need to identify and to scope their routines. This is a challenging endeavor in large organizations, as routines are usually not concentrated in a handful of processes, but rather scattered across the process landscape. Accordingly, the identification of routines from User Interaction (UI) logs has received significant attention. Existing approaches to this problem assume that the UI log is segmented, meaning that it consists of traces of a task that is presupposed to contain one or more routines. However, a UI log usually takes the form of a single unsegmented sequence of events. This paper presents an approach to discover candidate routines from unsegmented UI logs in the presence of noise, i.e. events within or between routine instances that do not belong to any routine. The approach is implemented as an open-source tool and evaluated using synthetic and real-life UI logs.
Year
DOI
Venue
2020
10.1109/ICPM49681.2020.00031
2020 2nd International Conference on Process Mining (ICPM)
Keywords
DocType
ISBN
Robotic process automation,robotic process mining,user interaction log
Conference
978-1-7281-9833-0
Citations 
PageRank 
References 
1
0.35
11
Authors
6
Name
Order
Citations
PageRank
V. Leno110.35
A. Augusto210.35
Marlon Dumas35742371.10
marcello la rosa4140281.70
F. Maggi510.35
A. Polyvyanyy610.35