Concept drift in process mining (PM) is a challenge as classical methods assume processes are in a steady-state, i.e., events share the same process version. We conducted a systematic literature review on the intersection of these areas, and thus, we review concept drift in PM and bring forward a taxonomy of existing techniques for drift detection and online PM for evolving environments. Existing works depict that (i) PM still primarily focuses on offline analysis, and (ii) the assessment of concept drift techniques in processes is cumbersome due to the lack of common evaluation protocol, datasets, and metrics.

中文翻译：

---

过程挖掘中的概念漂移调查

流程挖掘 (PM) 中的概念漂移是一个挑战，因为经典方法假设流程处于稳态，即事件共享相同的流程版本。我们对这些领域的交叉点进行了系统的文献回顾，因此，我们回顾了 PM 中的概念漂移，并提出了现有技术的分类法，用于漂移检测和在线 PM 以适应不断变化的环境。现有的工作描述了（i）PM 仍然主要侧重于离线分析，以及（ii）由于缺乏通用的评估协议、数据集和指标，流程中概念漂移技术的评估很麻烦。