论文标题
在盲点上阐明：开发参考体系结构以利用视频数据进行过程挖掘
Shedding Light on Blind Spots: Developing a Reference Architecture to Leverage Video Data for Process Mining
论文作者
论文摘要
流程挖掘是业务流程管理中最活跃的研究流之一。近年来，已经提出了许多用于分析结构化过程数据的方法。然而，在许多情况下，只有流程感知信息系统直接捕获的流程的数字化部分，而手动活动通常会导致盲点。尽管使用摄像机来观察这些活动可能有助于填补这一空白，但仍缺乏从非结构化视频数据中提取事件日志的标准化方法。在这里，我们提出了一个参考体系结构，以弥合计算机视觉和过程挖掘之间的差距。各种评估活动（即竞争性伪影分析，原型和现实世界应用）确保了所提出的参考体系结构允许灵活，用例驱动和上下文特定的实例化。我们的结果还表明，所提出的参考体系结构的示例性软件原型实例化能够自动从非结构化视频数据中自动提取大多数相关事件。
Process mining is one of the most active research streams in business process management. In recent years, numerous methods have been proposed for analyzing structured process data. Yet, in many cases, it is only the digitized parts of processes that are directly captured from process-aware information systems, and manual activities often result in blind spots. While the use of video cameras to observe these activities could help to fill this gap, a standardized approach to extracting event logs from unstructured video data remains lacking. Here, we propose a reference architecture to bridge the gap between computer vision and process mining. Various evaluation activities (i.e., competing artifact analysis, prototyping, and real-world application) ensured that the proposed reference architecture allows flexible, use-case-driven, and context-specific instantiations. Our results also show that an exemplary software prototype instantiation of the proposed reference architecture is capable of automatically extracting most of the process-relevant events from unstructured video data.
