The log skeleton miner (that is, the plugin called “Build Log Skeleton from Event Log”) in ProM 6.11 scores 98.3% on the PDC 2021 Data Set when the log skeleton is set to use 1% noise. When combined with the conversion to Petri nets (plugin called “Convert Log Skeleton to Petri Net”), which results in … [Read more…]
Do you believe you have implemented a good discovery algorithm? Then submit it to the PDC 2021 to put it to the test! If you submit your implemented discovery algorithm to the PDC 2021, and if your algorithm scores best on our data set of 480 training logs, then you win the contest! The contest … [Read more…]
The paper titled ‘The Log Skeleton Visualizer in ProM 6.9’ has been accepted for the journal ‘STTT Competitions and Challenges Track – TOOLympics 2019′. This paper introduces the winning contribution to the Process Discovery Contest of 2019 (PDC 2019), called the Log Skeleton Visualizer. This visualizer uses a novel type of process models called log … [Read more…]
The automated Process Discovery Contest of 2020 (PDC 2020) has been won by Sander Leemans with his discovery algorithm called the Directly Follows Model Miner. Congratulations to Sander!
The implementations for all discovery algorithms used for the Process Discovery Contest of 2020 (PDC 2020) have been disclosed: The 11 example implemented discovery algorithms for PDC 2020. The 10 submitted implemented discovery algorithms for PDC 2020. These algorithms all come with a Discover.bat file that runs the algorithm on the event log as given … [Read more…]
The data set of the Process Discovery Contest of 2020 (PDC 2020) has now been disclosed. It contains the following four folders (in ZIP archives): Ground Truth Logs: The test logs (.xes format) as classified by the corresponding models. Models: The original workflow nets (.pnml format) used to generate the logs. Test Logs: The logs … [Read more…]
Yesterday, I received the “Process Discovery Contest Award” for my winning submission to the Process Discovery Contest 2019. Many thanks to Massimiliano, Benoit, and Josep for organizing the contest. Next year, I will help them :-).
The nets I discovered for the Process Discovery Contest (PDC) 2019), classified 898 out of 900 correctly as fitting or non-fitting. Hence, I achieved with them a classification accuracy of 99.78%. Below, you’ll find all discovered nets. All nets are sound WF-nets. Both nets 9 and 10 classify a single trace wrongly. All nets were … [Read more…]
This screencast shows how the Log Skeleton Filter an Browser is used to ‘discover’ a sound WF net from training log 4 of the Process Discovery Challenge 2019.
Version 6.9.19 Version 6.9.19 of the PDC2019 package includes the final test logs. These can now be selected in the “Create PDC 2019 Log” plug-in. Documentation has been updated accordingly, see https://svn.win.tue.nl/trac/prom/browser/Documentation/PDC2019-6.9.19.pdf.
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