  Process mining has emerged as a way to analyze the behavior of an
organization by extracting knowledge from event logs and by offering techniques
to discover, monitor and enhance real processes. In the discovery of process
models, retrieving a complex one, i.e., a hardly readable process model, can
hinder the extraction of information. Even in well-structured process models,
there is information that cannot be obtained with the current techniques. In
this paper, we present WoMine, an algorithm to retrieve frequent behavioural
patterns from the model. Our approach searches in process models extracting
structures with sequences, selections, parallels and loops, which are
frequently executed in the logs. This proposal has been validated with a set of
process models, including some from BPI Challenges, and compared with the state
of the art techniques. Experiments have validated that WoMine can find all
types of patterns, extracting information that cannot be mined with the state
of the art techniques.
