Automatic discovery of object-centric behavioral constraint models

Abstract

Process discovery techniques have successfully been applied in a range of domains to automatically discover process models from event data. Unfortunately existing discovery techniques only discover a behavioral perspective of processes, where the data perspective is often as a second-class citizen. Besides, these discovery techniques fail to deal with object-centric data with many-to-many relationships. Therefore, in this paper, we aim to discover a novel modeling language which combines data models with declarative models, and the resulting object-centric behavioral constraint model is able to describe processes involving interacting instances and complex data dependencies. Moreover we propose an algorithm to discover such models.