Towards Goal-Oriented Process Mining

Mahdi Ghasemi
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引用次数: 5

Abstract

The growth of our digital world makes it possible to record many types of events. In particular, the number of business processes whose events are being logged is significantly increasing. Process mining is an approach that exploits event logs to discover real processes executed in organizations, enabling them to (re) design and improve process models. Goal modeling, on the other hand, is a requirements engineering approach mainly used to analyze what-if situations and support decision making. Common problems with process mining include the complexity of discovered "spaghetti" processes and a lack of goal-process alignment. Current process mining practices are mainly oriented towards activities and do not profit from considering stakeholder goals and requirements to manage complexity and alignment. Involving goal-related factors can augment the precision and interpretability of mined models and lead to better opportunities to satisfy stakeholders. In this research, I propose two methods (for goal-oriented process and enhancement discovery, and for conformance checking) that show potentially synergetic effects achievable by combining process mining and goal-oriented modeling. The paper reports on the research method, the gap/problems being addressed, preliminary solutions, expected contributions, and main foreseen challenges.
面向目标的过程挖掘
数字世界的发展使得记录各种类型的事件成为可能。特别是,记录其事件的业务流程的数量正在显著增加。流程挖掘是一种利用事件日志来发现组织中执行的实际流程的方法,使他们能够(重新)设计和改进流程模型。另一方面,目标建模是一种需求工程方法,主要用于分析假设情况并支持决策制定。过程挖掘的常见问题包括发现的“意大利面”过程的复杂性和缺乏目标-过程一致性。当前的过程挖掘实践主要面向活动,并不能从考虑涉众的目标和管理复杂性和一致性的需求中获益。涉及目标相关的因素可以提高挖掘模型的精度和可解释性,并带来更好的机会来满足利益相关者。在这项研究中,我提出了两种方法(面向目标的过程和增强发现,以及一致性检查),它们显示了通过结合过程挖掘和面向目标的建模可以实现的潜在协同效应。本文报告了研究方法、差距/正在解决的问题、初步解决方案、预期贡献和主要可预见的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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