Characterizing drift from event streams of business processes

Ostovar, Alireza, Maaradji, Abderrahmane, La Rosa, Marcello, & ter Hofstede, Arthur H.M. (2017) Characterizing drift from event streams of business processes. In 29th International Conference on Advanced Information Systems Engineering (CAiSE2017), 12-16 June 2017, Essen, Germany. (In Press)

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Abstract

Early detection of business process drifts from event logs enables analysts to identify changes that may negatively affect process performance. However, detecting a process drift without characterizing its nature is not enough to support analysts in understanding and rectifying process performance issues. We propose a method to characterize process drifts from event streams, in terms of the behavioral relations that are modified by the drift. The method builds upon a technique for online drift detection, and relies on a statistical test to select the behavioral relations extracted from the stream that have the highest explanatory power. The selected relations are then mapped to typical change patterns to explain the detected drifts. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in characterizing process drifts, and performs significantly better than alternative techniques.

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ID Code: 102264
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Concept drift, Process drift, Process drift characterization, Process mining, Business process management
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Engineering and Theory (080607)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Past > Schools > School of Information Systems
Copyright Owner: Copyright 2017 [please consult the author]
Deposited On: 07 Dec 2016 22:14
Last Modified: 20 Mar 2017 16:44

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