Abstract
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 most often try to abstract from the events in an automated way which does not capture the required domain knowledge to fit business activities. This can lead to misinterpretation of discovered process models. We developed an approach which aims to abstract an event log to the same abstraction level which is needed by the business. We use domain knowledge extracted from existing process documentation in order to automatically match events and activities. Our proposed abstraction approach is able to deal with n:m relations between events and activities and also supports concurrency. We evaluated our approach in a case study with a German IT outsourcing company.
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Baier, T., Mendling, J. (2013). Bridging Abstraction Layers in Process Mining by Automated Matching of Events and Activities. In: Daniel, F., Wang, J., Weber, B. (eds) Business Process Management. Lecture Notes in Computer Science, vol 8094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40176-3_4
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DOI: https://doi.org/10.1007/978-3-642-40176-3_4
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