Improving conformance checking in process modelling: a multiperspective algorithm

Abstract Business process model and notation (BPMN) is a popular used for modelling mainly due to its high expressiveness. However, BPMN has shortcomings when dealing with specific domains (namely Hazard Analysis Critical Control Points systems), struggling activity duration, quality control points, effects monitoring nature. To tackle these limitations, the business extended expressiveness (BPMN-E 2 ) was proposed. In this paper, multiperspective conformance checking algorithm developed focusing on detecting non-conformity between an event log model, regarding information provided by new elements within BPMN-E . The proposed follows two-step approach that starts converting into directly (annotated rules), which then in second phase perform effectively. This modular allows apply other notations than An clustering technique also downsize large-event logs without compromising data relevance. way, both log-downsize here are key contribution improve modelling, as evinced proof-of-concept provided.