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Log-based transactional workflow mining

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Abstract

A continuous evolution of business process parameters, constraints and needs, hardly foreseeable initially, requires a continuous design from the business process management systems. In this article we are interested in developing a reactive design through process log analysis ensuring process re-engineering and execution reliability. We propose to analyse workflow logs to discover workflow transactional behaviour and to subsequently improve and correct related recovery mechanisms. Our approach starts by collecting workflow logs. Then, we build, by statistical analysis techniques, an intermediate representation specifying elementary dependencies between activities. These dependencies are refined to mine the transactional workflow model. The analysis of the discrepancies between the discovered model and the initially designed model enables us to detect design gaps, concerning particularly the recovery mechanisms. Thus, based on this mining step, we apply a set of rules on the initially designed workflow to improve workflow reliability.

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Authors and Affiliations

  1. GET/INT (Institut National des Telecommunications), 9, Rue Charles Fourier, 91011, Evry, France

    Walid Gaaloul

  2. DERI-NUIG, IDA Business Park, Galway, Ireland

    Sami Bhiri, Armin Haller & Manfred Hauswirth

  3. SAP CEC Karlsruhe, Vincenz-Priessnitz-Strasse 1, 76131, Karlsruhe, Germany

    Khaled Gaaloul

  4. LORIA-INRIA-UMR 7503, BP 239, 54506, Vandœuvre-les-Nancy Cedex, France

    Khaled Gaaloul

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  1. Walid Gaaloul
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  2. Khaled Gaaloul
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  3. Sami Bhiri
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  4. Armin Haller
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  5. Manfred Hauswirth
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Correspondence to Walid Gaaloul.

Additional information

Communicated by Dimitrios Georgakopoulos.

The work presented in this paper was partially supported by the EU under the SUPER project (FP6-026850) and by the Lion project supported by Science Foundation Ireland under Grant No. SFI/02/CE1/I131.

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Gaaloul, W., Gaaloul, K., Bhiri, S. et al. Log-based transactional workflow mining. Distrib Parallel Databases 25, 193–240 (2009). https://doi.org/10.1007/s10619-009-7040-0

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