Metric trees for efficient similarity search in large process model repositories

Abstract

Due to the increasing adoption of business process management and the key role of process models, companies are setting up and maintaining large process model repositories. Repositories containing hundreds or thousands of process models are not uncommon, whereas only simplistic search functionality, such as text based search or folder navigation, is provided, today. On the other hand, advanced methods have recently been proposed in the literature to ascertain the similarity of process models. However, due to performance reasons, an exhaustive similarity search by pairwise comparison is not feasible in large process model repositories. This paper presents an indexing approach based on metric trees, a hierarchical search structure that saves comparison operations during search with nothing but a distance function at hand. A detailed investigation of this approach is provided along with a quantitative evaluation thereof, showing its suitability and scalability in large process model repositories. © 2011 Springer-Verlag.