Freezing Sub-Models During Incremental Process Discovery: Extended Version

TL;DR

This paper presents a novel incremental process discovery method that enables users to freeze parts of the model, allowing for more controlled and higher quality process models by incorporating user domain knowledge.

Contribution

It introduces a new approach that allows freezing sub-models during incremental discovery, enhancing user control and model quality.

Findings

Freezing sub-models improves process model quality.

User-guided freezing helps incorporate domain knowledge.

The approach outperforms previous incremental methods.

Abstract

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.