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Fast Incremental Conformance Analysis for Interactive Process Discovery

机译:交互式过程发现的快速增量一致性分析

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Interactive process discovery allows users to specify domain knowledge while discovering process models with the help of event logs. Typically the coherence of an event log and a process model is calculated using conformance analysis. Many state-of-the-art conformance techniques emphasize on the correctness of the results, and hence can be slow, impractical and undesirable in interactive process discovery setting, especially when the process models are complex. In this paper, we present a framework (and its application) to calculate conformance fast enough to guide the user in interactive process discovery. The proposed framework exploits the underlying techniques used for interactive process discovery in order to incrementally update the conformance results. We trade the accuracy of conformance for performance. However, the user is also provided with some diagnostic information, which can be useful for decision making in an interactive process discovery setting. The results show that our approach can be considerably faster than the traditional approaches and hence better suited in an interactive setting.
机译:交互式过程发现允许用户在事件日志的帮助下发现过程模型时指定领域知识。通常,事件日志和流程模型的一致性是使用一致性分析来计算的。许多最先进的一致性技术都强调结果的正确性,因此在交互过程发现设置中可能很慢,不切实际且不受欢迎,尤其是在过程模型复杂时。在本文中,我们提出了一个框架(及其应用程序)来足够快地计算一致性,以指导用户进行交互式过程发现。所提出的框架利用了用于交互过程发现的基础技术,以便逐步更新一致性结果。我们以一致性的准确性换取性能。但是,还为用户提供了一些诊断信息,这些信息对于交互式过程发现设置中的决策很有用。结果表明,我们的方法可以比传统方法快得多,因此更适合在交互式环境中使用。

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