Abstract
Most existing process mining algorithms have problems in dealing with invisible tasks. In this paper, a new process mining algorithm named α # is proposed, which extends the mining capacity of the classical α algorithm by supporting the detection of invisible tasks from event logs. Invisible tasks are first divided into four types according to their functional features, i.e., SIDE, SKIP, REDO and SWITCH. After that, the new ordering relation for detecting mendacious dependencies between tasks that reflects invisible tasks is introduced. Then the construction algorithms for invisible tasks of SIDE and SKIP/REDO/ SWITCH types are proposed respectively. Finally, the α # algorithm constructs the mined process models incorporating invisible tasks in WF-net. A lot of experiments are done to evaluate the mining quality of the proposed α # algorithm and the results are promising.
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Wen, L., Wang, J., Sun, J. (2007). Mining Invisible Tasks from Event Logs. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_38
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DOI: https://doi.org/10.1007/978-3-540-72524-4_38
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