Mining association rules to support resource allocation in business process management

Authors:
Zhengxing Huang;Xudong Lu;Huilong Duan
Affiliations:
College of Biomedical Engineering and Instrument Science of Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China;College of Biomedical Engineering and Instrument Science of Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China;College of Biomedical Engineering and Instrument Science of Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

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.