arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2001.01007cs.AI
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机器人过程自动化中数据转换的自动发现

Automated Discovery of Data Transformations for Robotic Process Automation

University of Melbourne(墨尔本大学);University of Tartu(塔尔图大学)

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

摘要:

机器人流程自动化(RPA)是一种用于自动化重复例程的技术,这些例程由用户与一个或多个应用程序的交互序列组成。为了充分利用RPA带来的机会,企业需要发现哪些特定的例程可以自动化,以及如何自动化。在这种情况下,本文解决了分析用户交互(UI)日志,以发现例程,用户从一个电子表格或(Web)的形式转移到另一个数据的问题。本文将这个问题映射到发现数据转换的例子-一个问题,其中有几种技术是可用的。该文件表明,一个天真的应用程序的最先进的数据转换发现的技术是计算效率低下。因此,本文提出了两种优化方法,它们利用了UI日志中的信息,以及跨应用程序的数据传输通常涉及分别复制字母和数字标记的事实。所提出的方法及其优化使用UI日志,复制现实生活中的重复数据传输例程进行评估。

英文摘要:

Robotic Process Automation (RPA) is a technology for automating repetitive routines consisting of sequences of user interactions with one or more applications. In order to fully exploit the opportunities opened by RPA, companies need to discover which specific routines may be automated, and how. In this setting, this paper addresses the problem of analyzing User Interaction (UI) logs in order to discover routines where a user transfers data from one spreadsheet or (Web) form to another. The paper maps this problem to that of discovering data transformations by example - a problem for which several techniques are available. The paper shows that a naive application of a state-of-the-art technique for data transformation discovery is computationally inefficient. Accordingly, the paper proposes two optimizations that take advantage of the information in the UI log and the fact that data transfers across applications typically involve copying alphabetic and numeric tokens separately. The proposed approach and its optimizations are evaluated using UI logs that replicate a real-life repetitive data transfer routine.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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