Local concurrency detection in business process event logs

Armas-Cervantes, Abel, La Rosa, Marcello, Dumas, Marlon, & Maaradji, Abderrahmane (2016) Local concurrency detection in business process event logs.

Abstract

Detecting concurrency relations between events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concurrency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over-generalization. This paper proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques.

Impact and interest:

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ID Code: 102438
Item Type: Report
Refereed: No
Additional URLs:
Keywords: process mining, concurrency theory, event structure, Petri net
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: Past > Schools > Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: 2016 The Author(s)
Deposited On: 14 Dec 2016 22:05
Last Modified: 15 Dec 2016 03:29

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