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Multidimensional Process Mining: Questions, Requirements, and Limitations

Abstract

Multidimensional process mining is an emerging approach that adopts the concept of data cubes to analyze processes from multi- ple views. This enables analysts to split event logs into a set of homoge- nous sublogs according to the case and event attributes. Each sublog is independently analyzed using process mining techniques resulting in an individual process model for each sublog. These models can be compared to identify group-related differences between the process variants. In this paper, we derive a number of general research questions addressed for multidimensional process mining by a literature review. We analyze the requirements for its application and point out its limitations and chal- lenges. We conduct two case studies applying multidimensional process mining in two different use cases to evaluate our findings.

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Citation
Category
Paper in Conference Proceedings or in Workshop Proceedings (Full Paper in Proceedings)
Event Title
CAISE 2016 Forum
Divisions
Workflow Systems and Technology
Event Location
Ljubljana
Event Type
Other
Event Dates
June 2016
Series Name
CAISE 2016 Forum
Page Range
pp. 169-176
Date
June 2016
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