Accepted publications

  • H. M. W. Verbeek, “The Log Skeleton Visualizer in ProM 6.9,” STTT, 2020.
    Title = {The {Log Skeleton Visualizer} in {ProM 6.9}},
    Author = {Verbeek, H. M. W.},
    Journal = {{STTT}},
    Year = {2020},
    Note = {Accepted for publication in 'STTT Competitions and Challenges Track - TOOLympics 2019'},
    Abstract = {Process discovery is an important area in the field of process mining. To help advance this area, a Process Discovery Contest (PDC) has been set up, which allows us to compare different approaches. At the moment of writing, there have been three instances of the PDC: In 2016, in 2017, and in 2019. This paper introduces the winning contribution to the PDC 2019, called the Log Skeleton Visualizer. This visualizer uses a novel type of process models called log skeletons. In contrast to many workflow-net-based discovery techniques, these log skeletons do not rely on the directly follows relation. As a result, log skeletons offer circumstantial information on the event log at hand rather than only sequential information. Using this visualizer we were able to classify 898 out of 900 traces correctly for the PDC 2019, and to win this contest.},
    Owner = {hverbeek},
    Timestamp = {2020.10.26}

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