Multi-perspective process mining

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    Process mining methods analyze an organization’s processes by using process execution data. During the handling of a process instance data about the execution of activities is recorded. Process mining uses such data to gain insights about the real execution of processes. In this thesis, we address research challenges in which a multi-perspective view on processes is needed and that look beyond the control-flow perspective, which defines the sequence of activities of a process. We consider problems in which multiple interacting process perspectives — in particular control-flow, data, resources, time, and functions — are considered together. The contributed methods span several types of process mining: two are concerned with conformance checking, two are process discovery techniques, and one is a decision mining method. All methods have been implemented, evaluated, and applied in the context of four case studies.

    Original languageEnglish
    Title of host publicationProceedings of the Dissertation Award, Demonstration, and Industrial Track at BPM 2018
    Subtitle of host publicationSydney, Australia, September 9-14, 2018.
    EditorsWil van den Aalst, Fabio Casati, Raffaele Conforti, Massimiliano de Leoni, Marlon Dumas, Akhil Kumar, Jan Mendling, Surya Nepal, Brian Pentland, Barbara Weber
    Number of pages5
    Publication statusPublished - 1 Jan 2018
    EventDissertation Award, Demonstration, and Industrial Track at BPM, BPMTracks 2018 - Sydney, Australia
    Duration: 9 Sep 201814 Sep 2018

    Publication series

    NameCEUR Workshop Proceedings
    ISSN (Print)1613-0073


    ConferenceDissertation Award, Demonstration, and Industrial Track at BPM, BPMTracks 2018
    Abbreviated titleBPMTracks 2018
    Internet address


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