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Lecture Notes in Computer Science
Existing process mining approaches are able to tolerate a certain degree of noise in process log. However, processes that contain infrequent paths, multiple (nested) parallel branches, or have been changed in an ad-hoc manner, still pose challenges. For such cases, process mining typically returns "spaghetti-models", that are hardly usable even as a starting point for process (re-)design. In this paper, we address these challenges by introducing data transformation and pre-processing steps thatdoi:10.1007/978-3-642-31095-9_16 fatcat:ygwpzjpkarhwbd7ddubr2qaowi