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OTM Confederated International Conferences "On the Move to Meaningful Internet Systems"

OTM 2016: On the Move to Meaningful Internet Systems: OTM 2016 Conferences pp 136–154Cite as

Process Instance Similarity: Potentials, Metrics, Applications

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10033))

Abstract

The analysis of process instance similarity offers valuable input for certain application fields including the evaluation of instance clusters, the identification of compliance abuses, and process optimization. In this paper, we discuss the topic of instance similarity in general: We show that similarity might be determined from different process perspectives such as control flow, time, and instance attributes. Each of these perspectives impose individual requirements on the similarity calculation concerning data and structure. Four metrics for process instance similarity are proposed covering different perspectives. The applicability and feasibility of the proposed metrics are evaluated based on a prototypical implementation and real-world process logs from the BPI challenges.

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Notes

  1. 1.

    http://www.xes-standard.org/.

  2. 2.

    If several end nodes are allowed by the respective meta model, the closest one is selected.

  3. 3.

    www.r-project.org.

  4. 4.

    http://www.promtools.org.

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Acknowledgments

This work has been funded by the Vienna Science and Technology Fund (WWTF) through project ICT15-072.

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Authors and Affiliations

  1. Faculty of Computer Science, University of Vienna, Vienna, Austria

    Johannes Pflug & Stefanie Rinderle-Ma

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  1. Johannes Pflug
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  2. Stefanie Rinderle-Ma
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Corresponding author

Correspondence to Johannes Pflug .

Editor information

Editors and Affiliations

  1. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Christophe Debruyne

  2. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. TU Graz, Graz, Austria

    Robert Meersman

  4. La Trobe University, Melbourne, Australia

    Tharam Dillon

  5. Institute of Computer Languages, TU Wien, Vienna, Austria

    eva Kühn

  6. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Declan O'Sullivan

  7. Università degli Studi di Milano Crema, Crema, Italy

    Claudio Agostino Ardagna

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Pflug, J., Rinderle-Ma, S. (2016). Process Instance Similarity: Potentials, Metrics, Applications. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-48472-3_8

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  • Online ISBN: 978-3-319-48472-3

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