A framework for interactive multidimensional process mining

Abstract

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.