Abstract
Engineering workflow applications are becoming more and more complex, involving numerous interacting business objects within considerable processes. Analysing the interaction structure of those complex applications will enable them to be well understood, controlled, and redesigned. Our contribution to workflow mining is a statistical technique to discover workflow patterns from event-based log. Our approach is characterised by a ”local” workflow patterns discovery that allows to cover partial results through a dynamic programming algorithm. Those local discovered workflow patterns are then composed iteratively until discovering the global workflow model. Our approach has been implemented within our prototype WorkflowMiner.
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Gaaloul, W., Baïna, K., Godart, C. (2006). A Bottom-Up Workflow Mining Approach for Workflow Applications Analysis. In: Lee, J., Shim, J., Lee, Sg., Bussler, C., Shim, S. (eds) Data Engineering Issues in E-Commerce and Services. DEECS 2006. Lecture Notes in Computer Science, vol 4055. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11780397_15
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DOI: https://doi.org/10.1007/11780397_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35440-6
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