论文标题
基于流的声明过程的监视和发现方法
A Monitoring and Discovery Approach for Declarative Processes Based on Streams
论文作者
论文摘要
过程发现是一种技术系列，有助于从其数据足迹中理解流程。然而，随着过程的随着时间的变化，它们的相应模型也会随着时间的流逝而发生变化，并且不这样做将导致模型不足或过度陈列的行为。我们提出了一种发现算法，该算法将声明过程从事件流中提取为动态条件响应（DCR）图。监视流以生成过程的时间表示，后来处理以生成声明模型。我们通过定量和定性评估验证了该技术。对于定量评估，我们采用了扩展的JACCARD相似性措施来说明声明环境中的过程变化。对于定性评估，我们展示了该技术确定的变化如何对应于现有过程中的实际变化。用于测试的技术和数据可在线获得。
Process discovery is a family of techniques that helps to comprehend processes from their data footprints. Yet, as processes change over time so should their corresponding models, and failure to do so will lead to models that under- or over-approximate behavior. We present a discovery algorithm that extracts declarative processes as Dynamic Condition Response (DCR) graphs from event streams. Streams are monitored to generate temporal representations of the process, later processed to generate declarative models. We validated the technique via quantitative and qualitative evaluations. For the quantitative evaluation, we adopted an extended Jaccard similarity measure to account for process change in a declarative setting. For the qualitative evaluation, we showcase how changes identified by the technique correspond to real changes in an existing process. The technique and the data used for testing are available online.
