Paper titled “Improving merging conditions for recomposing conformance checking” has been accepted for publication in BPI 2018

  • [PDF] W. L. J. Lee, J. Munoz-Gama, H. M. W. Verbeek, W. M. P. van der Aalst, and M. SepĂșlveda, “Improving merging conditions for recomposing conformance checking,” in Proceedings of the BPI 2018 workshop, 2018.
    [Bibtex]
    @InProceedings{Lee18,
    Title = {Improving merging conditions for recomposing conformance checking},
    Author = {Lee, W. L. J. and Munoz-Gama, J. and Verbeek, H. M. W. and Aalst, W. M. P. van der and Sep{\'u}lveda, M.},
    Booktitle = {Proceedings of the {BPI 2018} workshop},
    Year = {2018},
    Abstract = {Efficient conformance checking is a hot topic in the field of process mining. Much of the recent work focused on improving the scalability of alignment-based approaches to support the larger and more complex processes. This is needed because process mining is increasingly applied in areas where models and logs are “big”. Decomposition techniques are able to achieve significant performance gains by breaking down a conformance problem into smaller ones. Moreover, recent work showed that the alignment problem can be resolved in an iterative manner by alternating between aligning a set of decomposed subcomponents before merging the computed sub-alignments and recomposing subcomponents to fix merging issues. Despite experimental results showing the gain of applying recomposition in large scenarios, there is still a need for improving the merging step, where log traces can take numerous recomposition steps before reaching the required merging condition. This paper contributes by defining and structuring the recomposition step, and proposes strategies with significant performance improvement on synthetic and real-life datasets over both the state-of-the-art decomposed and monolithic approaches.},
    Owner = {hverbeek},
    Timestamp = {2018.06.27}
    }

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