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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23101

Title: PTandLogGenerator: a Generator for Artificial Event Data
Authors: Jouck, Toon
Depaire, Benoît
Issue Date: 2016
Citation: Azevedo, Leonardo; Cabanillas, Cristina (Ed.). Proceedings of the BPM Demo Track 2016 (BPMD 2016), CEUR workshop proceedings,p. 23-27 (Art N° 5)
Series/Report: CEUR workshop proceedings
Series/Report no.: 1789
Abstract: The empirical analysis of process discovery algorithms has recently gained more attention. An important step within such an analysis is the acquisition of the appropriate test event data, i.e. event logs and reference models. This requires an implemented framework that supports the random and automated generation of event data based on user speci cations. This paper presents a tool for generating arti cial process trees and event logs that can be used to study and compare the empirical workings of process discovery algorithms. It extends current tools by giving users full control over an extensive set of process control-flow constructs included in the fi nal models and event logs. Additionally, it is integrated within the ProM framework that o ffers a plethora of process discovery algorithms and evaluation metrics which are required during empirical analysis.
URI: http://hdl.handle.net/1942/23101
Link to publication: http://ceur-ws.org/Vol-1789/
ISSN: 1613-0073
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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