Mining batch processing workflow models from event logs

摘要

The employment of batch processing in workflow is to model and schedule activity instances in multiple workflow cases of the same workflow type to optimize business processes execution dynamically. Although our previous works have preliminarily investigated its model and implementation, it is still necessary to deal with its model design problem. Process mining techniques allow for the automated discovery of process models from event logs and have received notable attentions in researches recently. Following these researches, this paper proposes an approach to mine batch processing workflow models from event logs by considering the batch processing relations among activity instances in multiple workflow cases. The notion of batch processing feature and its corresponding mining algorithm are also presented for discovering the batch processing area in the model by using the input and output data information of activity instances in events. The algorithms presented in this paper can help to enhance the applicability of existing process mining approaches and broaden the process mining spectrum.