Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/26690
Title: | Generating Decision-Aware Models & Logs: Towards an Evaluation of Decision Mining | Authors: | JOUCK, Toon de Leoni, Massimiliano DEPAIRE, Benoit |
Issue Date: | 2018 | Source: | 6th International Workshop on Declarative/Decision/Hybrid Mining and Modelling for Business Processes (DeHMiMoP 2018), Sydney, Australia, 09-14/09/2018 | 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 to evaluate and compare 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/1942/26690 | Category: | C2 | Type: | Conference Material |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
paper.pdf | Conference material | 413.51 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.