面向意图的事件管理过程模型发现
Intention-Oriented Process Model Discovery from Incident Management Event Logs
摘要：
面向意图的过程挖掘是基于这样一种信念，即过程的基本性质大多是有意的（不同于面向活动的过程），旨在从过程制定期间记录的事件日志中发现策略和有意的过程模型。在本文中，我们提出了一个面向意图的过程挖掘领域的事件管理的信息技术基础设施库（ITIL）的过程。我们在一个大型的真实世界数据集上应用地图挖掘方法（MMM）来发现隐藏的和不可观察的用户行为，策略和意图。我们首先发现用户策略从给定的活动序列数据应用隐马尔可夫模型（HMM）的无监督学习技术。然后，我们处理发现的HMM的发射和转换矩阵，以生成一个粗粒度的映射过程模型。我们提出的第一个应用程序或研究的新的和新兴的领域面向意图的过程挖掘事件管理事件日志数据集，并讨论其适用性，有效性和挑战。
英文摘要：
Intention-oriented process mining is based on the belief that the fundamental nature of processes is mostly intentional (unlike activity-oriented process) and aims at discovering strategy and intentional process models from event-logs recorded during the process enactment. In this paper, we present an application of intention-oriented process mining for the domain of incident management of an Information Technology Infrastructure Library (ITIL) process. We apply the Map Miner Method (MMM) on a large real-world dataset for discovering hidden and unobservable user behavior, strategies and intentions. We first discover user strategies from the given activity sequence data by applying Hidden Markov Model (HMM) based unsupervised learning technique. We then process the emission and transition matrices of the discovered HMM to generate a coarse-grained Map Process Model. We present the first application or study of the new and emerging field of Intention-oriented process mining on an incident management event-log dataset and discuss its applicability, effectiveness and challenges.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
