The torrents of event data generated by today's systems are an important enabler for process mining. However, at the same time, the size and variability of the resulting event logs are challenging for today's process mining techniques. This paper focuses on "conformance checking in the large" and presents a novel decomposition technique that partitions larger processes into sets of subprocesses that can be analyzed more easily. The resulting topological representation of the partitioning can be used to localize conformance problems. Moreover, we provide techniques to refine the decomposition such that similar process fragments are not considered twice during conformance analysis. All the techniques have been implemented in ProM, and experimental results are provided.
Keywords: Process Mining, Conformance Checking, Process Diagnosis
|Number of pages||16|
|Publication status||Published - 2013|