论文标题
在线软符合检查：任何视角都可以表明偏差
Online Soft Conformance Checking: Any Perspective Can Indicate Deviations
论文作者
论文摘要
在过程挖掘中，相关的活动是一致性检查。这种活动包括确定过程的实际执行符合参考模型的预期行为的程度。当前的技术集中于控制流的规定模型作为参考。但是，在某些情况下，可能无法使用规范模型，此外，对于此目的而言，控制流的视角可能不是理想的选择。本文通过建议使用描述性模型（即，在一定时间内观察到的行为模式）提出一种符合性方法来解决这两个问题，这不一定是指控制流（例如，它可以基于工作移交的社交网络）。此外，整个方法都可以离线和在线工作，从而实时提供反馈。该方法已在PROM中实施，已经进行了测试，并报告了3个现实世界的实验以及合成数据的结果。
Within process mining, a relevant activity is conformance checking. Such activity consists of establishing the extent to which actual executions of a process conform the expected behavior of a reference model. Current techniques focus on prescriptive models of the control-flow as references. In certain scenarios, however, a prescriptive model might not be available and, additionally, the control-flow perspective might not be ideal for this purpose. This paper tackles these two problems by suggesting a conformance approach that uses a descriptive model (i.e., a pattern of the observed behavior over a certain amount of time) which is not necessarily referring to the control-flow (e.g., it can be based on the social network of handover of work). Additionally, the entire approach can work both offline and online, thus providing feedback in real time. The approach, which is implemented in ProM, has been tested and results from 3 experiments with real world as well as synthetic data are reported.
