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

OTM 2018: On the Move to Meaningful Internet Systems. OTM 2018 Conferences pp 318–335Cite as

Process Histories - Detecting and Representing Concept Drifts Based on Event Streams

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 11229)

Abstract

Business processes have to constantly adapt in order to react to changes induced by, e.g., new regulations or customer needs resulting in so called concept drifts. By now techniques to detect concept drifts are applied on process execution logs ex post, i.e., after the process is finished. However, detecting concept drifts during run-time bears many benefits such as instant reaction to the concept drift. Introducing process histories as a novel way to detect and represent incremental, sudden, recurring, and gradual concept drifts through mining the evolution of a process model based on an event stream will face this challenge. Therefore, a formal definition of process histories is given, the concept of process histories is prototypically implemented and compared with existing approaches based on a synthetic event log.

Keywords

  • Process mining
  • Event streams
  • Runtime
  • Concept drift
  • Process histories

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Notes

  1. 1.

    Extensible Event Stream.

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Acknowledgment

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

    Florian Stertz & Stefanie Rinderle-Ma

Authors
  1. Florian Stertz
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  2. Stefanie Rinderle-Ma
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Corresponding author

Correspondence to Florian Stertz .

Editor information

Editors and Affiliations

  1. CNRS, University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  2. Trinity College Dublin, Dublin, Ireland

    Christophe Debruyne

  3. Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg

    Henderik A. Proper

  4. Università degli Studi di Milano, Crema, Italy

    Dr. Claudio Agostino Ardagna

  5. SINTEF and University of Oslo, Oslo, Norway

    Dumitru Roman

  6. TU Graz, Graz, Austria

    Robert Meersman

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Stertz, F., Rinderle-Ma, S. (2018). Process Histories - Detecting and Representing Concept Drifts Based on Event Streams. In: Panetto, H., Debruyne, C., Proper, H., Ardagna, C., Roman, D., Meersman, R. (eds) On the Move to Meaningful Internet Systems. OTM 2018 Conferences. OTM 2018. Lecture Notes in Computer Science(), vol 11229. Springer, Cham. https://doi.org/10.1007/978-3-030-02610-3_18

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  • DOI: https://doi.org/10.1007/978-3-030-02610-3_18

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