在运行时关联未标记的事件（CS OH）---用户7095611

流程挖掘对于以数据为中心和以流程为中心的系统都非常重要。流程挖掘接收所谓的流程日志，它是部分有序事件的集合。事件必须至少具有三个属性，case ID、 task ID 和挖掘方法工作的时间戳。 当一个 case ID 是未知的时候，这个事件被称为未标记事件。 传统上，流程挖掘是一个离线任务，从不同来源收集的事件通常是手动相关的。也就是说，属于同一实例的事件被赋予相同的case ID。由于当今物联网应用的高容量 / 高速特性，进程挖掘转变成了一项在线任务。为此，事件相关性必须自动生成，并且必须在生成数据时发生。 在本文中，我们介绍了一种在运行时关联未标记事件的方法。 给定一个过程模型、一系列未标记事件以及其他关于任务持续时间的信息，我们的方法可以将一个案例标识符归纳为一组未标记事件，并给出一个信任百分比。它还可以检查确定的案例与过程模型的一致性，实现了该方法的原型，并根据实际生活和合成日志进行了评估。

原文题目：Correlating Unlabeled Events at Runtime

原文：Process mining is of great importance for both data-centric and process-centric systems. Process mining receives so-called process logs which are collections of partially-ordered events. An event has to possess at least three attributes, case ID, task ID and a timestamp for mining approaches to work. When a case ID is unknown, the event is called unlabeled. Traditionally, process mining is an offline task, where events are collected from different sources are usually manually correlated. That is, events belonging to the same instance are assigned the same case ID. With today's high-volume/high-speed nature of, e.g., IoT applications, process mining shifts to be an online task. For this, event correlation has to be automated and has to occur as the data is generated. In this paper, we introduce an approach that correlates unlabeled events at runtime. Given a process model, a stream of unlabeled events and other information about task duration, our approach can induce a case identifier to a set of unlabeled events with a trust percentage. It can also check the conformance of the identified cases with the process model. A prototype of the proposed approach was implemented and evaluated against real-life and synthetic logs.

原文作者：Iman Helal

原文地址：https://arxiv.org/abs/2004.09971