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Overlapping Analytic Stages in Online Process Mining

机译:在线过程挖掘中的重叠分析阶段

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Process mining uses business event logs to understand the flow of activities, to identify anomalous cases and to enhance processes. Today, real-time process mining tools mainly deal with a single task at a time (process discovery, conformance checking, process enhancement or concept change detection). In this paper, we introduce an underlined layer overlapping with multiple online process mining tasks to smooth their integration. Following a case clustering approach, based on trace and time analysis, our proposal supports simultaneously?: process discovery, conformance checking, and concept drift detection. We evaluated our approach and compared it with other techniques using both real-life and synthetic data, obtaining promising results.
机译:流程挖掘使用业务事件日志来了解活动流,识别异常情况并增强流程。如今,实时流程挖掘工具主要一次处理一个任务(流程发现,一致性检查,流程增强或概念更改检测)。在本文中,我们介绍了一个带有下划线的图层,该图层与多个在线流程挖掘任务重叠以平滑它们的集成。根据案例聚类方法,基于跟踪和时间分析,我们的建议同时支持以下内容:流程发现,一致性检查和概念漂移检测。我们评估了我们的方法,并将其与使用现实生活和综合数据的其他技术进行了比较,获得了可喜的结果。

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