Fast Business Process Similarity Search with Feature-Based Similarity Estimation

Nowadays, business process management plays an important role in the management of organizations. More and more organizations describe their operations as business processes, and the intra- and inter-organizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of business processes. Consequently, techniques are required to quickly find relevant business process models in such a collection. Currently, techniques exist that can rank all business process models in a collection based on their similarity to a query business process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as

relevant, irrelevant or potentially relevant

to a query model. Only

potentially relevant

models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.