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Encyclopedia of Big Data Technologies pp 1–10Cite as

Artifact-Centric Process Mining

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Synonyms

Multi-instance process mining; Object-centric process mining

Definition

Artifact-centric process mining is an extension of classical process mining (van der Aalst 2016) that allows to analyze event data with more than one case identifier in its entirety. It allows to analyze the dynamic behavior of (business) processes that create, read, update, and delete multiple data objects that are related to each other in relationships with one-to-one, one-to-many, and many-to-many cardinalities. Such event data is typically stored in relational databases of, for example, Enterprise Resource Planning (ERP) systems (Lu et al. 2015). Artifact-centric process mining comprises artifact-centric process discovery, conformance checking, and enhancement. The outcomes of artifact-centric process mining can be used for documenting the actual data flow in an organization and for analyzing deviations in the data flow for performance and conformance analysis.

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References

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Author information

Authors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Dirk Fahland

Authors
  1. Dirk Fahland
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Corresponding author

Correspondence to Dirk Fahland .

Editor information

Editors and Affiliations

  1. School of Comp. Sci. and Engineering, University of New South Wales School of Comp. Sci. and Engineering, Eveleigh, New South Wales, Australia

    Sherif Sakr

  2. Sch of Info Techno, Building J12, University of Sydney Sch of Info Techno, Building J12, Sydney, Australia

    Albert Zomaya

Section Editor information

  1. Institute of Computer Science, University of Tartu, Juhan Liivi 2, 50409, Tartu, Estonia

    Marlon Dumas

  2. Department of Computer Science, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany

    Matthias Weidlich

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Fahland, D. (2018). Artifact-Centric Process Mining. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_93-1

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  • DOI: https://doi.org/10.1007/978-3-319-63962-8_93-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63962-8

  • Online ISBN: 978-3-319-63962-8

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

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