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TESSERACT: Time-Drifts in Event Streams Using Series of Evolving Rolling Averages of Completion Times

  • Florian Richter
  • Thomas Seidl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10445)

Abstract

Business processes are dynamic and change due to diverse factors. While existing approaches aim to detect drifts in the process structure, TESSERACT looks for temporal drifts in activity interim times. This orthogonal view on the process extends the traditional data cube of events - case id, activities and timestamps - by a fourth dimension and improves the operational support by a visualization of temporal drifts in real-time.

Insights about temporal deviations lead to an augmented awareness of imminent failures or improved service times. The detection of related structural concept drifts can be improved by early warning, as operation times of critical parts often increase before they catastrophically fail.

Keywords

Process mining Event streams Temporal drift detection Operational support 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Ludwig-Maximilians-Universität MünchenMunichGermany

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