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A robust F-measure for evaluating discovered process models

机译:用于评估发现的过程模型的强大F度量

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Within process mining research, one of the most important fields of study is process discovery, which can be defined as the extraction of control-flow models from audit trails or information system event logs. The evaluation of discovered process models is an essential but difficult task for any process discovery analysis. With this paper, we propose a novel approach for evaluating discovered process models based on artificially generated negative events. This approach allows for the definition of a behavioral F-measure for discovered process models, which is the main contribution of this paper.
机译:在过程挖掘研究中,最重要的研究领域之一是过程发现,可以将其定义为从审计跟踪或信息系统事件日志中提取控制流模型。对于任何过程发现分析,对发现的过程模型的评估都是必不可少的但艰巨的任务。通过本文,我们提出了一种新方法,用于基于人为产生的负面事件评估发现的过程模型。这种方法可以为发现的过程模型定义行为F度量,这是本文的主要贡献。

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