Freezing Sub-Models During Incremental Process Discovery: Extended Version
This work addresses the need for more user control in process discovery algorithms, offering an incremental improvement for domain experts in business process management.
The paper tackles the problem of interactive process discovery by introducing a method that allows users to freeze sub-models during incremental model construction, preventing alterations when new behavior is added, and experiments show this can lead to higher quality models.
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.