Abstract. We investigate the problem of ranking all process models in a repository according to their similarity with respect to a given process model. We focus specifically on the application of graph matching algorithms to this similarity search problem. Since the corresponding graph matching problem is NP-complete, we seek to find a compromise between computational complexity and quality of the computed ranking. Using a repository of 100 process models, we evaluate four graph matching algorithms, ranging from a greedy one to a relatively exhaustive one. The results show that the mean average precision obtained by a fast greedy algorithm is close to that obtained with the most exhaustive algorithm.
Dijkman et al. REF investigated the similarity problem of process models centered on the structural aspect and proposed graph-matching algorithms for measuring similarities.
Graph matching algorithms for business process model similarity search
In Proc. International Conference on Business Process Management
Computer Science