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Checking Wrong Pattern in Process Model Containing Invisible Task by Using Declarative Miner

机译:使用声明式挖掘器检查包含隐形任务的流程模型中的错误模式

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Event log records all events of performed business process on the system. Analysts used the event log to detect occurred anomalies, one of which is wrong pattern, in the process. However, there are conditions, i.e. skip condition, redo condition, and switch condition, which can be misinterpreted as wrong pattern. Uniquely, those conditions cannot be depicted in the reference model without utilizing additional tasks, namely invisible tasks. This research proposes rules which can check the wrong pattern in the process model containing those conditions. This research automatically formed declarative miner rules carrying invisible tasks based on a process model. The form of the used process model in this research is a graph model. Then, the rules are used to checking the wrong pattern. The experiment uses real data, i.e. port-container handling processes, and several simulation data. The analysis explains that declarative miners have 100% accuracy to check the wrong pattern in the process model that contains each invisible task including skip condition, redo condition, and switch condition.
机译:事件日志记录系统上已执行的业务流程的所有事件。分析师使用事件日志来检测过程中发生的异常,其中之一是错误的模式。但是,存在一些条件,即跳过条件,重做条件和切换条件,这些条件可能会被误解为错误的模式。唯一地,如果不利用其他任务(即不可见任务),则无法在参考模型中描述这些条件。这项研究提出了可以检查包含这些条件的过程模型中错误模式的规则。该研究基于流程模型自动形成了声明性矿工规则,该规则承载了不可见的任务。本研究中使用的过程模型的形式是图模型。然后,使用规则检查错误的模式。实验使用实际数据(即端口容器处理过程)和一些模拟数据。分析说明,声明式矿工在包含每个不可见任务(包括跳过条件,重做条件和切换条件)的流程模型中检查错误模式的准确性为100%。

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