Abstract
An Approach for Mining Multiple Types of Silent Transitions in Business Process
Highlights
Nowadays, information system records the real execution of the business process in the form of event logs
Process discovery is the necessary technique for the other domains, which automatically constructs process models by applying the different discovery techniques on event logs [1]
Privacy-preservation issues of crossorganization business process mining[6,7], efficiency problem when dealing with large-scale event logs[8], process model discovery and process similarity measure considering both control-flow structures and data-flow information[9]
Summary
The existing process discovery algorithms have difficulties to discover possible silent tasks from the given event logs accurately and guarantee to return the appropriate result. They pay less attention to the behavioral relationship between activities in the event logs when detecting silent transitions. A novel approach to discover silent transitions based on the behavior distance is presented in the paper. The behavior distance between activities based on log, model, and concurrent structure is presented respectively to discover silent transitions accurately. 3. The novel approach to discover multiple silent transitions is proposed based on behavior distances and basic behavioral relations of event logs.
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