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Earth Movers' Stochastic Conformance Checking

机译:推土机的随机一致性检查

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摘要

Process Mining aims to support Business Process Management (BPM) by extracting information about processes from real-life process executions recorded in event logs. In particular, conformance checking aims to measure the quality of a process model by quantifying differences between the model and an event log or another model. Even though event logs provide insights into the likelihood of observed behaviour, most state-of-the-art conformance checking techniques ignore this point of view. In this paper, we propose a conformance measure that considers the stochastic characteristics of both the event log and the process model. It is based on the "earth movers' distance" and measures the effort to transform the distributions of traces of the event log into the distribution of traces of the model. We formalize this intuitive conformance metric and provide an approximation and a simplified variant. The latter two have been implemented in ProM and we evaluate them using several real-life examples.
机译:Process Mining旨在通过从事件日志中记录的实际流程执行中提取有关流程的信息来支持业务流程管理(BPM)。特别地,一致性检查旨在通过量化模型与事件日志或其他模型之间的差异来测量过程模型的质量。尽管事件日志提供了有关观察到的行为可能性的见解,但大多数最新的一致性检查技术都忽略了这一观点。在本文中,我们提出了一种一致性度量,该度量考虑了事件日志和过程模型的随机特征。它基于“地球移动者的距离”,并测量将事件日志的迹线分布转换为模型的迹线分布的工作量。我们将这种直观的一致性指标形式化,并提供一个近似值和一个简化的变体。后两个已在ProM中实现,我们将使用几个实际示例对它们进行评估。

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