Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/27128
Title: Using event log knowledge to support business process simulation model construction
Authors: MARTIN, Niels 
Issue Date: 2018
Source: van der Aalst, Wil; Casati, Fabio; Conforti, Raffaele; de Leoni, Massimiliano; Dumas, Marlon; Kumar, Akhil; Mending, Jan; Nepal, Surya; Pentland, Brian; Weber, Barbara (Ed.). Proceedings of the Dissertation Award, Demonstration, and Industrial Track at BPM 2018,p. 31-35
Series/Report: CEUR Workshop Proceedings
Series/Report no.: 2196
Abstract: My dissertation focuses on the use of event log knowledge, i.e. process mining, to support the development of business process simulation models. Despite the fact that the Process Mining Manifesto highlights this topic as a key research challenge, prior research efforts tend to have a proof-of-concept nature. To this end, this dissertation contributes towards fundamentally bridging the gap between these domains by (i) providing the required conceptualization and (ii) developing a set of methods that extract knowledge from event logs to support specific business process simulation modeling tasks.
Keywords: business process simulation; process mining
Document URI: http://hdl.handle.net/1942/27128
Link to publication/dataset: http://ceur-ws.org/Vol-2196/BPM_2018_paper_7.pdf
Category: C1
Type: Proceedings Paper
Validations: vabb 2020
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
paper7.pdfPublished version113.64 kBAdobe PDFView/Open
Show full item record

Page view(s)

42
checked on Sep 7, 2022

Download(s)

22
checked on Sep 7, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.