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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20239

Title: Capturing Process Behavior with Log-Based Process Metrics
Authors: Swennen, Marijke
Janssenswillen, Gert
Jans, Mieke J.
Depaire, Benoit
Vanhoof, Koen
Issue Date: 2015
Publisher: RWTH Aachen University
Citation: Ceravolo, Paolo; Rinderle-Ma, Stefanie (Ed.). Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis, p. 141-144
Series/Report: CEUR Workshop Proceedings
Series/Report no.: 1527
Abstract: Currently, process mining literature is primarily focused on the dis-covery of comprehensible process models that best capture the underlying behav-ior in event logs. Consequently, the resulting models a) aggregate information, based on algorithm-specific assumptions, and b) transform information into a simplified representation. Both characteristics, which are valuable in certain, dif-ferent contexts, suffer from the inability to describe objectively the behavior that is inherent to the event log at hand. In this paper, we present the need for log-based process metrics to capture the process behavior in an event log, without the need to first discover a model. The metrics provide a process owner with unbi-ased, algorithm-agnostic information of the event log, as a starting point of the process analysis. The constructed metrics also serve as a mean to objectively compare different event logs in terms of time-related and variance aspects.
URI: http://hdl.handle.net/1942/20239
Link to publication: http://ceur-ws.org/Vol-1527/paper12.pdf
ISSN: 1613-0073
Category: C1
Type: Proceedings Paper
Validation: vabb, 2017
Appears in Collections: Research publications

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