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Detection of batch activities from event logs
Information Systems ( IF 3.7 ) Pub Date : 2020-09-10 , DOI: 10.1016/j.is.2020.101642
Niels Martin , Luise Pufahl , Felix Mannhardt

Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this event log to discover the process’ control-flow, its performance, information about the resources, etc. A common assumption is that the cases are executed independently of each other. However, batch work – the collective execution of cases for specific activities – is a common phenomenon in operational processes to save costs or time. Existing research has mainly focused on discovering individual batch tasks. However, beyond this narrow setting, batch processing may consist of the execution of several linked tasks. In this work, we present a novel algorithm which can also detect parallel, sequential and concurrent batching over several connected tasks, i.e., subprocesses. The proposed algorithm is evaluated on synthetic logs generated by a business process simulator, as well as on a real-world log obtained from a hospital’s digital whiteboard system. The evaluation shows that batch processing at the subprocess level can be reliably detected.



中文翻译:

从事件日志中检测批处理活动

组织执行各种业务流程以服务其客户。通常由信息技术和系统支持,流程执行数据记录在事件日志中。流程挖掘使用此事件日志来发现流程的控制流,其性能,有关资源的信息等。通常的假设是,案例彼此独立地执行。但是,批处理工作(针对特定活动共同执行案例)是操作流程中常见的现象,可以节省成本或时间。现有研究主要集中在发现单个批处理任务上。但是,除此狭窄的设置外,批处理可能包括执行几个链接的任务。在这项工作中,我们提出了一种新颖的算法,该算法还可以检测并行,在几个连接的任务(即子流程)上进行顺序和并发批处理。在业务流程模拟器生成的综合日志以及从医院的数字白板系统获得的真实日志中,对提出的算法进行了评估。评估表明,可以可靠地检测子过程级别的批处理。

更新日期:2020-09-10
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