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      Identifying candidate routines for Robotic Process Automation from unsegmented UI logs

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          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.

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          Author and article information

          Journal
          13 August 2020
          Article
          2008.05782
          3a746a0c-643b-497b-a417-b74963c8cecd

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          International Conference on Process Mining 2020
          cs.SE

          Software engineering
          Software engineering

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