This paper presents SECPI (Search for Explanations of Clusters of Process Instances), a technique that assists users with understanding a trace clustering solution by finding a minimal set of control-flow characteristics whose absence would prevent a process instance from remaining in its current cluster. As such, the shortcoming of current trace clustering techniques regarding the provision of insight into the computation of a particular partitioning is addressed by learning concise individual rules that clearly explain why a certain instance is part of a cluster.
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