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Estimation of Average Latent Waiting and Service Times of Activities from Event Logs

机译:从事件日志中估计活动的平均潜在等待和服务时间

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Analysis of performance is crucial in the redesign phase of business processes where bottlenecks are identified from the average waiting and service times of activities and resources in business processes. However, such averages of waiting and service times are not readily available in most event logs that only record either the start or the completion times of events in activities. The transition times between events in such logs are the only performance features that are available. This paper proposes a novel method of estimating the average latent waiting and service times from the transition times that employs the optimization of the likelihood of the probabilistic model with expectation and maximization (EM) algorithms. Our experimental results indicated that our method could estimate the average latent waiting and service times with sufficient accuracy to enable practical applications through performance analysis.
机译:在业务流程的重新设计阶段中,对性能进行分析至关重要,在该阶段中,从业务流程中活动和资源的平均等待和服务时间确定瓶颈。但是,在大多数仅记录活动中事件开始或完成时间的事件日志中,这样的平均等待时间和服务时间并不容易获得。此类日志中事件之间的过渡时间是唯一可用的性能功能。本文提出了一种从过渡时间估计平均潜在等待和服务时间的新方法,该方法采用了具有期望和最大化(EM)算法的概率模型的似然性优化。我们的实验结果表明,我们的方法可以足够准确地估计平均潜在等待和服务时间,以通过性能分析使实际应用成为可能。

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