While the maturity of process mining algorithms increases and more process
mining tools enter the market, process mining projects still face the
problem of different levels of abstraction when comparing events with modeled
business activities. Current approaches for event log abstraction try to
abstract from the events in an automated way that does not capture the
required domain knowledge to fit business activities. This can lead to misinterpretation
of discovered process models. We developed an approach that
aims to abstract an event log to the same abstraction level that is needed
by the business. We use domain knowledge extracted from existing process
documentation to semi-automatically match events and activities. Our abstraction
approach is able to deal with n:m relations between events and
activities and also supports concurrency. We evaluated our approach in two
case studies with a German IT outsourcing company.
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:4394 |
| Date | 12 1900 |
| Creators | Baier, Thomas, Mendling, Jan, Weske, Mathias |
| Publisher | Elsevier |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, NonPeerReviewed |
| Format | application/pdf |
| Relation | http://dx.doi.org/10.1016/j.is.2014.04.004, http://www.elsevier.com/, http://epub.wu.ac.at/4394/ |
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