HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Finding Suitable Activity Clusters for Decomposed Process Discovery

Abstract : Event data can be found in any information system and provide the starting point for a range of process mining techniques. The widespread availability of large amounts of event data also creates new challenges. Existing process mining techniques are often unable to handle “big event data” adequately. Decomposed process mining aims to solve this problem by decomposing the process mining problem into many smaller problems which can be solved in less time, using less resources, or even in parallel. Many decomposed process mining techniques have been proposed in literature. Analysis shows that even though the decomposition step takes a relatively small amount of time, it is of key importance in finding a high-quality process model and for the computation time required to discover the individual parts. Currently there is no way to assess the quality of a decomposition beforehand. We define three quality notions that can be used to assess a decomposition, before using it to discover a model or check conformance with. We then propose a decomposition approach that uses these notions and is able to find a high-quality decomposition in little time.
Document type :
Conference papers
Complete list of metadata

Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Friday, January 20, 2017 - 3:39:14 PM
Last modification on : Friday, January 20, 2017 - 3:41:56 PM
Long-term archiving on: : Friday, April 21, 2017 - 3:46:10 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



B. Hompes, H. Verbeek, W. Aalst. Finding Suitable Activity Clusters for Decomposed Process Discovery. 4th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Nov 2014, Milan, Italy. pp.32-57, ⟨10.1007/978-3-319-27243-6_2⟩. ⟨hal-01442339⟩



Record views


Files downloads