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Discovering high-level BPMN process models from event data

机译：从事件数据中发现高级BPMN流程模型

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Purpose The purpose of this paper is to demonstrate that process mining techniques can help to discover process models from event logs, using conventional high-level process modeling languages, such as Business Process Model and Notation (BPMN), leveraging their representational bias. Design/methodology/approach The integrated discovery approach presented in this work is aimed to mine: control, data and resource perspectives within one process diagram, and, if possible, construct a hierarchy of subprocesses improving the model readability. The proposed approach is defined as a sequence of steps, performed to discover a model, containing various perspectives and presenting a holistic view of a process. This approach was implemented within an open-source process mining framework called ProM and proved its applicability for the analysis of real-life event logs. Findings This paper shows that the proposed integrated approach can be applied to real-life event logs of information systems from different domains. The multi-perspective process diagrams obtained within the approach are of good quality and better than models discovered using a technique that does not consider hierarchy. Moreover, due to the decomposition methods applied, the proposed approach can deal with large event logs, which cannot be handled by methods that do not use decomposition. Originality/value The paper consolidates various process mining techniques, which were never integrated before and presents a novel approach for the discovery of multi-perspective hierarchical BPMN models. This approach bridges the gap between well-known process mining techniques and a wide range of BPMN-complaint tools.
机译：目的本文的目的是证明流程挖掘技术可以利用常规的高级流程建模语言（例如业务流程模型和表示法（BPMN）），利用它们的表示偏差，帮助从事件日志中发现流程模型。设计/方法/方法本工作中提出的集成发现方法旨在挖掘：在一个流程图中的控制，数据和资源方面的观点，并在可能的情况下构建子流程的层次结构，以提高模型的可读性。所提出的方法被定义为一系列步骤，执行这些步骤以发现一个模型，其中包含各种视角并提供流程的整体视图。该方法在名为ProM的开源过程挖掘框架中实现，并证明了其在分析实际事件日志中的适用性。调查结果本文表明，所提出的集成方法可以应用于来自不同领域的信息系统的真实事件日志。在该方法中获得的多角度流程图具有良好的质量，并且比使用不考虑层次的技术发现的模型更好。此外，由于采用了分解方法，因此所提出的方法可以处理大型事件日志，而大型事件日志无法通过不使用分解的方法来处理。独创性/价值本文整合了以前从未集成过的各种流程挖掘技术，并提出了一种用于发现多角度分层BPMN模型的新颖方法。这种方法弥合了众所周知的流程挖掘技术与各种BPMN投诉工具之间的鸿沟。

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