  Process discovery aims to learn a process model from observed process
behavior. From a user's perspective, most discovery algorithms work like a
black box. Besides parameter tuning, there is no interaction between the user
and the algorithm. Interactive process discovery allows the user to exploit
domain knowledge and to guide the discovery process. Previously, an incremental
discovery approach has been introduced where a model, considered to be under
construction, gets incrementally extended by user-selected process behavior.
This paper introduces a novel approach that additionally allows the user to
freeze model parts within the model under construction. Frozen sub-models are
not altered by the incremental approach when new behavior is added to the
model. The user can thus steer the discovery algorithm. Our experiments show
that freezing sub-models can lead to higher quality models.
