Abstract
Process mining algorithms, designed for real world data, typically cope with noisy or incomplete logs via techniques that force the analyst to set the value of several parameters. Because of that, many process models corresponding to different parameters settings can be generated, and the analyst gets very easily lost in such a variety of process models. In order to have really effective algorithms, it is of paramount importance to give to the analyst the possibility to easily interpret the output of the mining.
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Notes
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It must be stressed that a process may be ill-defined even if no such couples of relations are present at the same time.
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Visit http://www.win.tue.nl/coselog for more information.
- 3.
The tool is freely available at http://www.cpntools.org.
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Burattin, A. (2015). Results Interpretation and Evaluation. In: Process Mining Techniques in Business Environments. Lecture Notes in Business Information Processing, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-319-17482-2_15
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DOI: https://doi.org/10.1007/978-3-319-17482-2_15
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-17482-2
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