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Fast Incremental Conformance Analysis for Interactive Process Discovery

机译:交互式进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活动日志的帮助下发现进程模型时指定域知识。通常,使用一致性分析计算事件日志和过程模型的相干性。许多最先进的一致性技术强调了结果的正确性,因此在交互式过程发现设置中可以缓慢,不切实无缺,特别是当过程模型复杂时。在本文中,我们介绍了一个框架(及其应用程序)来计算足够快的一致性,以指导用户在交互过程发现中。所提出的框架利用用于交互过程发现的底层技术,以便逐步更新一致性结果。我们交易表现一致性的准确性。然而,用户还提供了一些诊断信息,这对于在交互式过程发现设置中的决策中可以是有用的。结果表明,我们的方法可以比传统方法更快,因此更适合交互式环境。

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