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.
Original language | English |
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Title of host publication | Business Process Management Workshops - BPM 2018 International Workshops, Revised Papers |
Editors | Florian Daniel, Quan Z. Sheng, Hamid Motahari |
Place of Publication | Cham |
Publisher | Springer |
Pages | 482-493 |
Number of pages | 12 |
ISBN (Electronic) | 978-3-030-11641-5 |
ISBN (Print) | 978-3-030-11640-8 |
DOIs | |
Publication status | Published - 29 Jan 2019 |
Event | 16th International Conference on Business Process Management (BPM 2018) - Sydney, Australia Duration: 9 Sep 2018 → 14 Sep 2018 Conference number: 16 http://ceur-ws.org/Vol-2196/ |
Publication series
Name | Lecture Notes in Business Information Processing |
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Volume | 342 |
ISSN (Print) | 1865-1348 |
Conference
Conference | 16th International Conference on Business Process Management (BPM 2018) |
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Abbreviated title | BPM 2018 |
Country/Territory | Australia |
City | Sydney |
Period | 9/09/18 → 14/09/18 |
Other | Dissertation Award, Demonstration, and Industrial Track at BPM |
Internet address |
Keywords
- Decision mining
- Evaluation
- Log generation