Predicting the quality of process model matching

Abstract

Process model matching refers to the task of creating correspondences among activities of different process models. This task is crucial whenever comparison and alignment of process models are called for. In recent years, there have been a few attempts to tackle process model matching. Yet, evaluating the obtained sets of correspondences reveals high variability in the results. Addressing this issue, we propose a method for predicting the quality of results derived by process model matchers. As such, prediction serves as a case-by-case decision making tool in estimating the amount of trust one should put into automatic matching. This paper proposes a model of prediction for process matching based on both process properties and preliminary match results. © 2013 Springer-Verlag.