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doi: 10.5281/zenodo.19227
This set of processes, built for test purposes [1], is composed of 125 process models. These processes were created using PLG [2, 3]. The generation of the random processes is based on some basic “process patterns”, like the AND-split/join, XORsplit/join, the sequence of two activities, and so on. For each of the 125 process models, two logs were generated: one with 250 traces and one with 500 traces. In these logs, the 75% of the activities are expressed as time intervals (the other ones are instantaneous) and 5% of the traces are noise. In this context “noise” is considered either a swap between two activities or removal of an activity. References A. Burattin, A. Sperduti. "Automatic Determination of Parameters Values' for Heuristics Miner++". In Proceedings of IEEE Congress on Evolutionary Computation (IEEE WCCI CEC 2010); 10.1109/CEC.2010.5586208 A. Burattin. “PLG2: Multiperspective Processes Randomization and Simulation for Online and Offline Settings”. In CoRR abs/1506.08415, Jun. 2015. A. Burattin and A. Sperduti. “PLG: a Framework for the Generation of Business Process Models and their Execution Logs”. In Proc. of the 6th Int. Workshop on Business Process Intelligence (BPI 2010); 2010.10.1007/978-3-642-20511-8_20.
process mining, petri nets, process models, artificial dataset, event log
process mining, petri nets, process models, artificial dataset, event log
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