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Using Image Mining Techniques from a Business Process Perspective

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Book cover Enterprise Information Systems (ICEIS 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 417))

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Abstract

Business process modeling is an established method to improve business procedures and to provide more insights into internal workflows. Once the process is visualized in a business process model, future process executions correspond to the workflow prescribed by the process model. Process details like input specifications or the order of internal sub-steps are only considered during process execution if contained in the process model. These details may be decisive since they can have an impact on the success of the overall process. In some cases, such important process details are not modeled due to different aspects, like modeling with a high degree of abstraction to preserve the traceability. Nevertheless, it is necessary to identify missing but essential process details that reduce the success rate of a process. In this paper, we present a conceptual approach to use image mining techniques in order to analyze and extract process details from image data recorded during process executions. We propose to redesign business process models considering the analysis results to ensure successful process executions. We discuss different requirements regarding the image analysis output and present an exemplary prototype.

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Author information

Authors and Affiliations

  1. University of Bayreuth, Bayreuth, Germany

    Myriel Fichtner & Stefan Jablonski

  2. University of Regensburg, Regensburg, Germany

    Stefan Schönig

Authors
  1. Myriel Fichtner
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  2. Stefan Schönig
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  3. Stefan Jablonski
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Corresponding authors

Correspondence to Myriel Fichtner , Stefan Schönig or Stefan Jablonski .

Editor information

Editors and Affiliations

  1. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. George Mason University, Fairfax, VA, USA

    Alexander Brodsky

  4. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

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Fichtner, M., Schönig, S., Jablonski, S. (2021). Using Image Mining Techniques from a Business Process Perspective. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2020. Lecture Notes in Business Information Processing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-030-75418-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-75418-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-75417-4

  • Online ISBN: 978-3-030-75418-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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