It is common for large and complex organizations to maintain repositories of business process models in order to document and to continuously improve their operations. Given such a repository, this paper deals with the problem of retrieving those process models in the repository that most closely resemble a given process model or fragment thereof. The paper presents three similarity metrics that can be used to answer such queries: (i) label matching similarity that compares the labels attached to process model elements; (ii) structural similarity that compares element labels as well as the topology of process models; and (iii) behavioral similarity that compares element labels as well as causal relations captured in the process model. These similarity metrics are experimentally evaluated in terms of precision and recall, and in terms of correlation of the metrics with respect to human judgement. The experimental results show that all three metrics yield comparable results, with structural similarity slightly outperforming the other two metrics. Also, all three metrics outperform traditional search engines when it comes to searching through a repository for similar business process models
