A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
Lecture Notes in Business Information Processing
Multidimensional process mining adopts the concept of data cubes to split event data into a set of homogenous sublogs according to case and event attributes. For each sublog, a separated process model is discovered and compared to other models to identify group-specific differences for the process. Even though it is not time-critical, performance is vital due to the explorative characteristics of the analysis. We propose to adopt well-established approaches from the data warehouse domain baseddoi:10.1007/978-3-319-53435-0_8 fatcat:4f7yg45jxvahfive6srypbsiji