Clustering Business Process Activities for Identifying Reference Model Components

Abstract

Reference models are special conceptual models that are reused for the design of other conceptual models. They confront stakeholders with the dilemma of balancing the size of a model against its reuse frequency. The larger a reference model is, the better it applies to a specific situation, but the less often these situations occur. This is particularly important when mining a reference model from large process logs, as this often produces complex and unstructured models. To address this dilemma, we present a new approach for mining reference model components by vertically dividing complex process traces and hierarchically clustering activities based on their proximity in the log. We construct a hierarchy of subprocesses, where the lower a component is placed the smaller and the more structured it is. The approach is implemented as a proof-of-concept and evaluated using the data from the 2017 BPI challenge.