Associate Professor
Technical University of Denmark
Within process mining, we can identify conformance checking as the task of computing the extent to which executions of a process model are in line with the reference behavior. Most approaches currently available in the literature (for imperative models, such as Petri nets) perform just a-posteriori analyses. This means that the amount of non-conformant behavior is quantified after the completion of the current execution. The tool presented in this paper, instead, proposes an approach for online conformance checking: not only it is capable of quantifying the deviating behavior on the fly, but the computation complexity is also restricted to a constant complexity per event analyzed. This enables the online analysis of an infinite stream of events. The tool is implemented as a package of the ProM framework and promising results have been obtained and are presented in this paper.
In Online Proceedings of the BPM Demo Track 2017; Barcelona, Spain; September 10-15, 2017; CEUR-WS.org 2017.
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