Automatic discovery of object-centric behavioral constraint models

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    Process discovery techniques have successfully been applied in a range of domains to automatically discover process models from event data. Unfortunately existing discovery techniques only discover a behavioral perspective of processes, where the data perspective is often as a second-class citizen. Besides, these discovery techniques fail to deal with object-centric data with many-to-many relationships. Therefore, in this paper, we aim to discover a novel modeling language which combines data models with declarative models, and the resulting object-centric behavioral constraint model is able to describe processes involving interacting instances and complex data dependencies. Moreover we propose an algorithm to discover such models.

    Original languageEnglish
    Title of host publicationBusiness Information Systems
    Subtitle of host publication20th International Conference, BIS 2017, Poznan, Poland, June 28–30, 2017, Proceedings
    EditorsW. Abramowicz
    Place of PublicationDordrecht
    Number of pages16
    ISBN (Electronic)978-3-319-59336-4
    ISBN (Print)978-3-319-59335-7
    Publication statusPublished - 21 Jun 2017
    Event20th International Conference on Business Information Systems, (BIS 2017), 28-30 June 2017, Poznan, Poland - Poznan, Poland
    Duration: 28 Jun 201730 Jun 2017

    Publication series

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


    Conference20th International Conference on Business Information Systems, (BIS 2017), 28-30 June 2017, Poznan, Poland
    Abbreviated titleBIS 2017
    Internet address


    • Cardinality constraints
    • Object-centric modeling
    • Process discovery
    • Process mining


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