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Data Improvement to Enable Process Mining on Integrated Non-log Data Sources

机译:数据改进使过程挖掘在集成的非日志数据源上

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Process models derived using Process Mining (PM) are often very complex due to Data Quality Issues (DQIs). Some of those DQIs arise from integration of different data sources or the transformation of non-process oriented data, hence are structural and can be abstracted from the domain. Activity Sequencing and Activity Hierarchy are two concepts for improving certain DQIs in order to improve PM outcomes. The approaches are evaluated by showing the improvement of derived process models using a simplified real world scenario with simulated data.
机译:由于数据质量问题(DQI),使用流程挖掘(PM)导出的过程模型通常非常复杂。其中一些DQIS来自集成不同的数据源或非过程导向数据的转换,因此是结构性的,可以从域中抽象。活动排序和活动层次是改进某些DQI的两个概念,以便改善PM结果。通过使用具有模拟数据的简化的真实世界场景来说明推导过程模型的改进来评估该方法。

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