Using life cycle information in process discovery

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    17 Citations (Scopus)
    1 Downloads (Pure)


    Understanding the performance of business processes is an important part of any business process intelligence project. From historical information recorded in event logs, performance can be measured and visualized on a discovered process model. Thereby the accuracy of the measured performance, e.g., waiting time, greatly depends on (1) the availability of start and completion events for activities in the event log, i.e. transactional information, and (2) the ability to differentiate between subtle control flow aspects, e.g. concurrent and interleaved execution. Current process discovery algorithms either do not use activity life cycle information in a systematic way or cannot distinguish subtle controlflow aspects, leading to less accurate performance measurements. In this paper, we investigate the automatic discovery of process models from event logs, such that performance can be measured more accurately. We discuss ways of systematically treating life cycle information in process discovery and their implications. We introduce a process discovery technique that is able to handle life cycle data and that distinguishes concurrency and interleaving. Finally, we show that it can discover models and reliable performance information from event logs only.

    Original languageEnglish
    Title of host publicationBusiness Process Management Workshops
    Subtitle of host publicationBPM 2015, 13th International Workshops, Innsbruck, Austria, August 31 – September 3, 2015, Revised Papers
    EditorsM. Reichert, H.A. Reijers
    Place of PublicationDordrecht
    Number of pages14
    ISBN (Electronic)978-3-319-42887-1
    ISBN (Print)978-3-319-42886-4
    Publication statusPublished - 2016
    Event13th International Workshops on Business Process Management Workshops (BPM 2015) - Innsbruck, Austria
    Duration: 31 Aug 20153 Sep 2015
    Conference number: 13

    Publication series

    NameLecture Notes in Business Information Processing
    ISSN (Print)18651348


    Conference13th International Workshops on Business Process Management Workshops (BPM 2015)
    Abbreviated titleBPM 2015
    Internet address


    • Concurrency
    • Performance measurement
    • Process discovery
    • Process mining
    • Rediscoverability

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