SECPI: Searching for Explanations for Clustered Process Instances

Abstract

Abstract. 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.

Detecting Changes in Process Behavior Using Comparative Case Clustering

“…This can, for example, indicate that behavior has become more specific or more general. Besides visual approaches, techniques such as [20] that aim to explain clusters of cases can be used as well.…”