论文标题
以对象为中心的过程预测分析
Object-centric Process Predictive Analytics
论文作者
论文摘要
以对象为中心的过程（又称以人工为中心的过程）是一个范式的实现，其中一个过程的实例不是孤立地执行，而是与相同或其他过程的其他实例进行交互。互动是通过实例交换数据的桥接事件进行的。以对象为中心的过程最近在学术界和行业中越来越受欢迎，因为在许多应用程序方面都可以观察到它们的性质。由于过程实例的复杂性，通过多一对众多的关联相互关联，这对预测分析提出了重大挑战。现有的研究无法直接利用这些相互作用的好处，从而限制了预测质量。本文提出了一种将有关对象相互作用的信息纳入预测模型的方法。使用不同的KPI对以对象为中心的过程事件数据进行评估该方法。将结果与忽略对象相互作用的天真方法进行了比较，从而说明了它们在预测质量上的使用的好处。
Object-centric processes (a.k.a. Artifact-centric processes) are implementations of a paradigm where an instance of one process is not executed in isolation but interacts with other instances of the same or other processes. Interactions take place through bridging events where instances exchange data. Object-centric processes are recently gaining popularity in academia and industry, because their nature is observed in many application scenarios. This poses significant challenges in predictive analytics due to the complex intricacy of the process instances that relate to each other via many-to-many associations. Existing research is unable to directly exploit the benefits of these interactions, thus limiting the prediction quality. This paper proposes an approach to incorporate the information about the object interactions into the predictive models. The approach is assessed on real-life object-centric process event data, using different KPIs. The results are compared with a naive approach that overlooks the object interactions, thus illustrating the benefits of their use on the prediction quality.
