With the increasing influence of Business Process Management, large process model repositories emerged in enterprises and public administrations. Their effective utilization requires meaningful and efficient capabilities to search for models that go beyond text based search or folder navigation, e.g., by similarity. Existing measures for process model similarity are often not applicable for efficient similarity search, as they lack metric features. In this paper, we introduce a proper metric to quantify process similarity based on behavioral profiles. It is grounded in the Jaccard coefficient and leverages behavioral relations between pairs of process model activities. The metric is successfully evaluated towards its approximation of human similarity assessment. © 2011 Springer-Verlag.
CITATION STYLE
Kunze, M., Weidlich, M., & Weske, M. (2011). Behavioral similarity - A proper metric. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6896 LNCS, pp. 166–181). https://doi.org/10.1007/978-3-642-23059-2_15
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