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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/30171
- A semi-automatic approach for workflow staff assignment
- Liu, Yingbo; Wang, Jianmin; Yang, Yun; Sun, Jiaguang
- Staff assignment is of great importance for workflow management systems. In many workflow applications, staff assignment is still performed manually. In this paper, we present a semi-automatic approach intended to reduce the number of manual staff assignment. Our approach applies a machine learning algorithm to the workflow event log to learn various kinds of activities that each actor undertakes. When staff assignment is needed, the classifiers generated by the machine learning technique suggest a suitable actor to undertake the specified activities. With experiments on three enterprises, our approach achieved a fairly accurate recommendation.
- Publication type
- Journal article
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies. Centre for Information Technology Research
- Computers in Industry, Vol. 59, no. 5 (May 2008), p. 463-476
- Publication year
- Machine learning; Resource management; Staff assignment; Workflow
- Publisher URL
- Copyright © 2008 Elsevier B.V. All rights reserved.
- Peer reviewed