Improving merging conditions for recomposing conformance checking

Wai Lam Jonathan Lee, Jorge Munoz-Gama, H.M.W. Verbeek, Wil M.P. van der Aalst, Marcos Sepúlveda

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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    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 sub-components before merging the computed sub-alignments and recomposing sub-components 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.

    Originele taal-2Engels
    TitelBusiness Process Management Workshops - BPM 2018 International Workshops, Revised Papers
    RedacteurenFlorian Daniel, Quan Z. Sheng, Hamid Motahari
    Plaats van productieCham
    Aantal pagina's13
    ISBN van elektronische versie978-3-030-11641-5
    ISBN van geprinte versie978-3-030-11640-8
    StatusGepubliceerd - 1 jan 2019
    Evenement16th International Conference on Business Process Management, BPM 2018 - Sydney, Australië
    Duur: 9 sep 201814 sep 2018

    Publicatie series

    NaamLecture Notes in Business Information Processing
    ISSN van geprinte versie1865-1348


    Congres16th International Conference on Business Process Management, BPM 2018

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