Automatic root cause identification using most probable alignments

M. Koorneef, A. Solti, H. Leopold, H.A. Reijers

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    5 Citations (Scopus)
    1 Downloads (Pure)


    In many organizational contexts, it is important that behavior conforms to the intended behavior as specified by process models. Non-conforming behavior can be detected by aligning process actions in the event log to the process model. A probable alignment indicates the most likely root cause for non-conforming behavior. Unfortunately, available techniques do not always return the most probable alignment and, therefore, also not the most probable root cause. Recognizing this limitation, this paper introduces a method for computing the most probable alignment. The core idea of our approach is to use the history of an event log to assign probabilities to the occurrences of activities and the transitions between them. A theoretical evaluation demonstrates that our approach improves upon existing work.

    Original languageEnglish
    Title of host publicationBusiness Process Management Workshops - BPM 2017 International Workshops, Barcelona, Spain, September 10-11, 2017, Revised Papers
    EditorsE. Teniente, M. Weidlich
    Place of PublicationCham
    Number of pages12
    ISBN (Electronic) 9783319740300
    ISBN (Print)9783319740294
    Publication statusPublished - 2018
    Event15th International Conference on Business Process Management (BPM 2017) - Barcelona, Spain
    Duration: 10 Sep 201715 Sep 2017
    Conference number: 15

    Publication series

    NameLecture Notes in Business Information Processing
    ISSN (Print)1865-1348


    Conference15th International Conference on Business Process Management (BPM 2017)
    Abbreviated titleBPM 2017
    Internet address


    • Conformance checking
    • Most probable alignments
    • Root cause analysis
    • Root cause analysis Most probable alignments

    Fingerprint Dive into the research topics of 'Automatic root cause identification using most probable alignments'. Together they form a unique fingerprint.

    Cite this