Mining local process models

@article{Tax2016MiningLP,
  title={Mining local process models},
  author={Niek Tax and N. Sidorova and R. Haakma and W. Aalst},
  journal={ArXiv},
  year={2016},
  volume={abs/1606.06066}
}
In this paper we describe a method to discover frequent behavioral patterns in event logs. We express these patterns as \emph{local process models}. Local process model mining can be positioned in-between process discovery and episode / sequential pattern mining. The technique presented in this paper is able to learn behavioral patterns involving sequential composition, concurrency, choice and loop, like in process mining. However, we do not look at start-to-end models, which distinguishes our… Expand
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Heuristic approaches for generating Local Process Models through log projections
On the Use of Hierarchical Subtrace Mining for Efficient Local Process Model Mining
Mining Frequent Patterns in Process Models
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