Abstract
Staff assignment of workflow is often performed manually and empirically. In this paper we propose an optimal approach named SAHMM ( Staff Assignment based on Hidden Markov Models ) to allocate the most proficient set of employees for a whole business process based on workflow event logs. The Hidden Markov Model( HMM ) is used to describe the complicated relationships among employees which are ignored by previous approaches. The validity of the approach is confirmed by experiments on real data.
This research was partially supported by the National Key Basic Research Program of China (No. 2002CB312006, No. 2007CB310802), the National High Technology Research and Development Program of China (No. 2008AA042301) and the National Natural Science Foundation of China (No. 90718010).
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Yang, H., Wang, C., Liu, Y., Wang, J. (2008). An Optimal Approach for Workflow Staff Assignment Based on Hidden Markov Models. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2008 Workshops. OTM 2008. Lecture Notes in Computer Science, vol 5333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88875-8_12
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DOI: https://doi.org/10.1007/978-3-540-88875-8_12
Publisher Name: Springer, Berlin, Heidelberg
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