提出混合流程框架概念，揭示其可自动发现的潜力。
On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery
- 将流程框架视为程序与声明式模型的混合体。
- 发现不同流程行为对应特定的Declare约束模式。
- 为自动化流程发现提供新思路，适合流程挖掘研究者。
任何人工智能增强型业务流程管理系统（ABPMS）的核心是流程框架，它赋予系统流程感知能力并定义其最大行为边界。与传统流程模型相比，流程框架原则上应提供更宽松的表示，以支持（半）自主行为的涌现，即‘框架自治’。此外，流程框架不限于单一语言或符号形式，可融合从预定义规程到常识规则和最佳实践的异构知识。本文首次将ABPMS流程框架概念化为一种混合业务流程表示，包含半并发执行的程序式与声明式流程模型，并将声明范式中的开放世界假设扩展至程序模型。这允许任意一组（无冲突）的两种类型模型组合执行，但增加了从事件数据中自动发现这些模型的难度。现有程序模型方法尤其受影响，因其依赖直接跟随关系的观察。为此，我们深入分析了不同程序行为如何表现为一组发现的Declare约束，每种对应特定的最终跟随关系。该分析揭示了声明式与程序模型间的语义重叠，也为开发相应的流程（框架）发现技术奠定了基础。
原文摘要 · Abstract (English)
A core component of any AI-Augmented Business Process Management System (ABPMS) is the process frame, which gives the system process-awareness and defines its maximal behavioral boundaries. Compared to traditional process models, the process frame should, in principle, provide a somewhat more permissive representation of the managed processes, such that the (semi) autonomous behavior of an ABPMS, referred to as framed autonomy, could emerge. In addition, the process frame is not limited to a single linguistic or symbolic formalism and may incorporate heterogeneous knowledge ranging from predefined procedures to common sense rules and best practices. In this paper, we first conceptualize the ABPMS process frame as a hybrid business process representation, consisting of semi-concurrently executed procedural and declarative process models, extending the open-world assumption of the declarative paradigm also to procedural models. The latter allows any set of (non-conflicting) models of either type to be combined for execution, but complicates the automated discovery of these models from event data. Existing approaches for procedural models are particularly affected due to their reliance on observing directly-follows relations between pairs of activities. In search of an alternative, we present an in-depth analysis of how different procedural behaviors manifest as sets of discovered Declare constraints, each corresponding to a specific type of eventually-follows relation. This reveals behavioral overlaps between declarative and procedural models, while also laying the foundation for developing corresponding process (frame) discovery techniques.
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