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Overlapping analytic stages in online process mining

Tavares G.M.
•
Ceravolo P.
•
Da Costa V.G.T.
altro
Barbon Junior S
2019
  • conference object

Abstract
Process mining uses business event logs to understand the flow of activities, to identify anomalous cases and to enhance processes. Today, real-time process mining tools mainly deal with a single task at a time (process discovery, conformance checking, process enhancement or concept change detection). In this paper, we introduce an underlined layer overlapping with multiple online process mining tasks to smooth their integration. Following a case clustering approach, based on trace and time analysis, our proposal supports simultaneously?: process discovery, conformance checking, and concept drift detection. We evaluated our approach and compared it with other techniques using both real-life and synthetic data, obtaining promising results.
DOI
10.1109/SCC.2019.00037
WOS
WOS:000556202100024
Archivio
https://hdl.handle.net/11368/3004548
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85072572058
https://ieeexplore.ieee.org/document/8813959
Diritti
closed access
license:copyright editore
license uri:iris.pri02
FVG url
https://arts.units.it/request-item?handle=11368/3004548
Soggetti
  • business data process...

  • data mining

  • pattern clustering

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