Using automatic planning to find the most probable alignment: A history-based approach

Abstract

In many organizational contexts, the existence of a normative process model makes it possible to verify if the actual execution of activities of a business process conforms to that model. Non-conforming behavior can be detected by aligning the actions recorded in the event log with a related normative process model. The alignment approach uses a cost-function to build an execution path that shows which actions do not conform to the model, and which are the expected activities for that trace. In this paper, we are interested on finding the optimal probable alignment using a history-base cost-function, i.e. a function based on the process execution history. For that, we use as a base implementation the planning-based approach, previously proposed in the literature, which demonstrates to find large processes faster when compared to A* for standard cost-functions. We incorporate in this tool the automatic generation of an history-base cost-function to find an optimal probable alignment. In addition, we evaluated our approach using data from both synthetic event logs and a real-life event log.