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A Framework for Interactive Multidimensional Process Mining

机译:交互式多维过程挖掘框架

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The emerging concept of multidimensional process mining adopts the ideas of data cubes and OLAP to analyze processes from multiple views. Analysts can split the event log into a set of homogenous sublogs according to its case and event attributes. Process mining techniques are used to create an individual process model for each sublog representing variants of the process. These models can be compared to identify the differences between the variants. Due to the explorative character of the analysis, interactivity is crucial to successfully apply multidimensional process mining. However, current approaches lack interactivity, e.g., they require the analyst to re-perform the analysis steps after changing the view on the data cube. In this paper, we introduce a novel framework to improve the interactivity of multidimensional process mining. As our main contribution, we provide a generic concept for interactive process mining based on a stack of operations.
机译:多维过程挖掘的新兴概念采用数据多维数据集和OLAP的思想来分析来自多种视图的过程。分析师可以根据其案例和事件属性将事件登录分成一组同质的子抄写员。处理挖掘技术用于为代表该过程的变体创建单个过程模型。可以比较这些模型以识别变体之间的差异。由于分析的探索性,相互作用对于成功应用多维过程采矿至关重要。然而,当前方法缺少交互性,例如,它们要求分析师在更改数据多维数据集的视图后重新执行分析步骤。在本文中,我们介绍了一种新颖的框架来改善多维过程采矿的交互性。作为我们的主要贡献,我们为基于一堆操作的互动过程挖掘提供了一般概念。

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