Mining association rules to support resource allocation in business process management

Resource allocation is of great importance for business process management. In business process execution, a set of rules that specify resource allocation is always implied. Although many approaches have been offered to support resource allocation, they are not sufficient to derive interesting resource allocation rules which ensure that each activity is performed by suitable resource. Hence, this paper introduces an association rule mining based approach to mine interesting resource allocation rules from event log. The idea is to concern the ordered correlations between items in event log, and then to present two efficient algorithms to mine real “interesting” rules. The event log of radiology CT-scan examination process provided by the Chinese Huzhou hospital is used to verify the proposed approach. The evaluation results showed that the proposed approach not only is able to extract the rules more efficient and much faster, but also can discover more important resource allocation rules.

Research highlights
► This study presents two efficient algorithms to mining resource allocation rules in business processes.
► The algorithms are verified by actual event logs of radiology CT-scan examination process provided by the Chinese Huzhou center hospital.
► The method allows for more efficient and effective resource allocations in business process management.