  Processes, such as patient pathways, can be very complex, comprising of
hundreds of activities and dozens of interleaved subprocesses. While existing
process discovery algorithms have proven to construct models of high quality on
clean logs of structured processes, it still remains a challenge when the
algorithms are being applied to logs of complex processes. The creation of a
multi-level, hierarchical representation of a process can help to manage this
complexity. However, current approaches that pursue this idea suffer from a
variety of weaknesses. In particular, they do not deal well with interleaving
subprocesses. In this paper, we propose FlexHMiner, a three-step approach to
discover processes with multi-level interleaved subprocesses. We implemented
FlexHMiner in the open source Process Mining toolkit ProM. We used seven
real-life logs to compare the qualities of hierarchical models discovered using
domain knowledge, random clustering, and flat approaches. Our results indicate
that the hierarchical process models that the FlexHMiner generates compare
favorably to approaches that do not exploit hierarchy.
