Process mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions, which is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they do not aim at providing efficient solutions; or (iii) the discovered process models are difficult to read due to the number of assignment conditions included. In this paper we address these problems and develop an efficient and effective process mining framework that provides extensive support for the discovery of patterns related to resource assignment. The framework is validated in terms of performance and applicability.
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:5684 |
| Date | 23 June 2016 |
| Creators | Schönig, Stefan, Cabanillas Macias, Cristina, Jablonski, Stefan, Mendling, Jan |
| Publisher | Elsevier |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Relation | http://dx.doi.org/10.1016/j.dss.2016.06.012, https://www.journals.elsevier.com/decision-support-systems, https://www.elsevier.com/journals/decision-support-systems/0167-9236/open-access-options, http://epub.wu.ac.at/5684/ |
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