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Time prediction on multi-perspective declarative business processes

机译：多视角陈述业务流程的时间预测

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摘要

Process-aware information systems (PAISs) are increasingly used to provide flexible support for business processes. The support given through a PAIS is greatly enhanced when it is able to provide accurate time predictions which is typically a very challenging task. Predictions should be (1) multi-dimensional and (2) not based on a single process instance. Furthermore, the prediction system should be able to (3) adapt to changing circumstances and (4) deal with multi-perspective declarative languages (e.g., models which consider time, resource, data and control flow perspectives). In this work, a novel approach for generating time predictions considering the aforementioned characteristics is proposed. For this, first, a multi-perspective constraint-based language is used to model the scenario. Thereafter, an optimized enactment plan (representing a potential execution alternative) is generated from such a model considering the current execution state of the process instances. Finally, predictions are performed by evaluating a desired function over this enactment plan. To evaluate the applicability of our approach in practical settings we apply it to a real process scenario. Despite the high complexity of the considered problems, results indicate that our approach produces a satisfactory number of good predictions in a reasonable time.
机译：过程感知信息系统（PAISS）越来越多地用于为业务流程提供灵活的支持。通过PAI给出的支持在能够提供通常是一个非常具有挑战性的任务的准确时间预测时大大提高了。预测应为（1）多维和（2）不基于单个流程实例。此外，预测系统应该能够（3）适应不断变化的情况和（4）处理多透视陈述语言（例如，考虑时间，资源，数据和控制流程透视图的模型）。在这项工作中，提出了考虑上述特征的产生时间预测的新方法。为此，首先，使用基于多视角约束的语言来模拟方案。此后，考虑到过程实例的当前执行状态，从这种模型生成优化的制定计划（表示潜在的执行替代方案）。最后，通过在该制定计划上评估期望的功能来执行预测。为了评估我们在实际设置中的方法的适用性，我们将其应用于真实的过程场景。尽管所考虑的问题具有很高的复杂性，但结果表明我们的方法在合理的时间内产生了令人满意的良好预测。

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