Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/28409
Title: | A Framework to Evaluate and Compare Decision-Mining Techniques | Authors: | JOUCK, Toon de Leoni, Massimiliano DEPAIRE, Benoit |
Issue Date: | 2019 | Publisher: | Springer Inernational Publishing | Source: | Daniel, Florian; Sheng, Quan Z.; Motahari, Hamid (Ed.). Business Process Management Workshops, Springer Inernational Publishing,p. 482-493 | Series/Report: | Lecture Notes in Business Information Processing | Series/Report no.: | 342 | Abstract: | During the last decade several decision mining techniques have been developed to discover the decision perspective of a process from an event log. The increasing number of decision mining techniques raises the importance of evaluating the quality of the discovered decision models and/or decision logic. Currently, the evaluations are limited because of the small amount of available event logs with decision information. To alleviate this limitation, this paper introduces the `DataExtend' technique that allows evaluating and comparing decision-mining techniques with each other, using a sufficient number of event logs and process models to generate evaluation results that are statistically significant. This paper also reports on an initial evaluation using `DataExtend' that involves two techniques to discover decisions, whose results illustrate that the approach can serve the purpose. | Keywords: | Decision mining; Evaluation; Log generation | Document URI: | http://hdl.handle.net/1942/28409 | ISBN: | 978-3-030-11641-5 | DOI: | 10.1007/978-3-030-11641-5_38 | Rights: | Springer Nature Switzerland AG 2019 | Category: | C1 | Type: | Proceedings Paper | Validations: | vabb 2021 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
paper.pdf Restricted Access | Peer-reviewed author version | 413.51 kB | Adobe PDF | View/Open Request a copy |
Page view(s)
288
checked on Sep 7, 2022
Download(s)
256
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.