论文标题
从未分段的UI日志中识别机器人过程自动化的候选程序
Identifying candidate routines for Robotic Process Automation from unsegmented UI logs
论文作者
论文摘要
机器人过程自动化（RPA）是一项技术，可以开发软件机器人，该机器人可以自动化用户和软件应用程序之间的交互重复序列（又称例程）。为了充分利用这项技术，组织需要识别和范围范围。在大型组织中，这是一项艰巨的努力，因为常规通常不是集中在少数过程中，而是散布在整个过程景观中。因此，从用户交互（UI）日志中识别例程已受到了极大的关注。现有的该问题的方法假定UI日志已被分割，这意味着它由一个任务的痕迹组成，该任务被以包含一个或多个例程的前提。但是，UI日志通常采用单个未分段的事件序列的形式。本文提出了一种在存在噪声的情况下从未分段的UI日志中发现候选例程的方法，即不属于任何例程的例行实例内或之间的事件。该方法作为开源工具实现，并使用合成和现实生活中的UI日志进行评估。
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.
