A bottom-up workflow mining approach for workflow applications analysis

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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 iterativety until discovering the global workflow model. Our approach has been implemented within our prototype WorkflowMiner. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Gaaloul, W., Baïna, K., & Godart, C. (2006). A bottom-up workflow mining approach for workflow applications analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4055 LNCS, pp. 182–197). Springer Verlag. https://doi.org/10.1007/11780397_15

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