Process mining aims at discovering processes by extracting knowledge about their different perspectives from event logs. The resource perspective (or organisational perspective) deals, among others, with the assignment of resources to process activities. Mining in relation to this perspective aims to extract rules on resource assignments for the process activities. Prior research in this area is limited by the assumption that only one resource is responsible for each process activity, and hence, collaborative activities are disregarded. In this paper, we leverage this assumption by developing a process mining approach that is able to discover team compositions for collaborative process activities from event logs. We evaluate our novel mining approach in terms of computational performance and practical applicability.
Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:5685 |
Date | 22 October 2016 |
Creators | Schönig, Stefan, Cabanillas Macias, Cristina, Di Ciccio, Claudio, Jablonski, Stefan, Mendling, Jan |
Publisher | Springer Berlin Heidelberg |
Source Sets | Wirtschaftsuniversität Wien |
Language | English |
Detected Language | English |
Type | Article, PeerReviewed |
Format | application/pdf |
Relation | http://dx.doi.org/10.1007/s10270-016-0567-4, https://link.springer.com/journal/10270, http://www.springer.com/de/open-access/authors-rights/self-archiving-policy/2124, http://epub.wu.ac.at/5685/ |
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