Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/17963
Title: Generating Artificial Event Logs with Sufficient Discriminatory Power to Compare Process Discovery Techniques
Authors: JOUCK, Toon 
DEPAIRE, Benoit 
Issue Date: 2014
Publisher: CEUR
Source: Ceravolo, Paolo; Accorsi, Rafael; Russo, Barbara (Ed.). Proceedings of the 4th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2014), p. 174-178
Series/Report: CEUR Workshop Proceedings
Series/Report no.: 1293
Abstract: Past research revealed issues with artificial event data used for comparative analysis of process mining algorithms. The aim of this research is to design, implement and validate a framework for producing artificial event logs which should increase discriminatory power of artificial event logs when evaluating process discovery techniques.
Notes: This paper is a research plan
Keywords: artificial event logs; event log simulation; performance measurement of business processes
Document URI: http://hdl.handle.net/1942/17963
Link to publication/dataset: http://ceur-ws.org/Vol-1293/
Rights: Creative Commons License
Category: C1
Type: Proceedings Paper
Validations: vabb 2016
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
SIMPDA- paper 13.pdfPeer-reviewed author version133.53 kBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check


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