Discovering hierarchical process models using ProM

Abstract

Process models can be seen as "maps" describing the operational processes of organizations. Traditional process discovery algorithms have problems dealing with fine-grained event logs and less-structured processes. The discovered models (i.e., "maps") are spaghetti-like and are difficult to comprehend or even misleading. One of the reasons for this can be attributed to the fact that the discovered models are flat (without any hierarchy). In this paper, we demonstrate the discovery of hierarchical process models using a set of interrelated plugins implemented in ProM. The hierarchy is enabled through the automated discovery of abstractions (of activities) with domain significance. © 2012 Springer-Verlag.