Organizations execute decisions within business processes on a daily basis whilst having to take into account multiple stakeholders who might require multiple point of views of the same process. Moreover, the complexity of the information systems running these business processes is generally high as they are linked to databases storing all the relevant data and aspects of the processes. Given the presence of multiple objects within an information system which support the processes in their enactment, decisions are naturally influenced by both these perspectives, logged in object-centric process logs. However, the discovery of such decisions from object-centric process logs is not straightforward as it requires to correctly link the involved objects whilst considering the sequential constraints that business processes impose as well as correctly discovering what a decision actually does. This paper proposes the first object-centric decision-mining algorithm called Integrated Object-centric Decision Discovery Algorithm (IODDA). IODDA is able to discover how a decision is structured as well as how a decision is made. Moreover, IODDA is able to discover which activities and object types are involved in the decision-making process. Next, IODDA is demonstrated with the first artificial knowledge-intensive process logs whose log generators are provided to the research community.

翻译：组织在日常执行业务流程中的决策时，必须考虑多个利益相关者，这些利益相关者可能对同一流程有不同视角的要求。此外，运行这些业务流程的信息系统通常具有很高的复杂性，因为它们与存储所有相关数据和流程方面数据的数据库相关联。考虑到信息系统中存在支持流程实施的多重对象，决策自然会受到这两种视角的影响——这些视角记录在面向对象的过程日志中。然而，从面向对象的过程日志中挖掘此类决策并非易事，因为需要正确关联涉及的对象，同时考虑业务流程施加的顺序约束，并准确发现决策的实际内容。本文提出了首个面向对象的决策挖掘算法，即集成式面向对象决策发现算法（IODDA）。IODDA能够发现决策的结构以及决策的制定方式。此外，IODDA还能识别参与决策过程的活动和对象类型。接下来，IODDA通过首个包含生成器的人工知识密集型过程日志进行演示，这些日志生成器已提供给研究社区。