Discovering Hierarchical Consolidated Models from Process Families
Process families consist of different related variants that represent the same process. This might include, for example, processes executed similarly by different organizations or different versions of a same process with varying features. Motivated by the need to manage variability in process families, recent advances in process mining make it possible to discover, from a collection of event logs, a generic process model that explicitly describes the commonalities and differences across variants. However, existing approaches often result in flat complex models where it is hard to obtain a comparative insight into the common and different parts, especially when the family consists of a large number of process variants. This paper presents a decomposition-driven approach to discover hierarchical consolidated process models from collections of event logs. The discovered hierarchy consists of nested process fragments and allows to browse the variability at different levels of abstraction. The approach has been implemented as a plugin in ProM and was evaluated using synthetic and real-life event logs.
KeywordsProcess mining Consolidated process families Hierarchical configurable models Decomposed discovery Configurable fragments
- 7.La Rosa, M., Dumas, M., Uba, R., Dijkman, R.: Business process model merging: an approach to business process consolidation. ACM Trans. Softw. Eng. Methodol. 22(2), 11:1–11:42 (2013)Google Scholar
- 8.Johnson, R., Pearson, D., Pingali, K.: The program structure tree: computing control regions in linear time. In: Proceedings of the ACM SIGPLAN 1994 Conference on Programming Language Design and Implementation (PLDI), pp. 171–185 (1994)Google Scholar
- 17.Reichert, M., Kolb, J., Bobrik, R., Bauer, T.: Enabling personalized visualization of large business processes through parameterizable views. In: Proceedings of the ACM Symposium on Applied Computing, SAC 2012, Riva, Trento, Italy, 26–30 March 2012, pp. 1653–1660 (2012)Google Scholar
- 19.van Dongen, B.F.: BPI challenge 2015 (2015). http://dx.doi.org/10.4121/uuid:31a308ef-c844-48da-948c-305d167a0ec1