Evaluation Goals for Online Process Mining: A Concept Drift Perspective

Paolo Ceravolo, Gabriel Marques Tavares, Sylvio Barbon Junior, Ernesto Damiani

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Online process mining refers to a class of techniques for analyzing in real-time event streams generated by the execution of business processes. These techniques are crucial in the reactive monitoring of business processes, timely resource allocation and detection/prevention of dysfunctional behavior. Many interesting advances have been made by the research community in recent years, but there is no consensus on the exact set of properties these techniques have to achieve. This article fills the gap by identifying a set of evaluation goals for online process mining and examining their fulfillment in the state of the art. We discuss parameters and techniques regulating the balance between conflicting goals and outline research needed for their improvement. Concept drift detection is crucial in this sense but, as demonstrated by our experiments, it is only partially supported by current solutions.

Original languageBritish English
Pages (from-to)2473-2489
Number of pages17
JournalIEEE Transactions on Services Computing
Volume15
Issue number4
DOIs
StatePublished - 2022

Keywords

  • concept drift
  • event stream
  • Online process mining
  • requirements and goals

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