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http://hdl.handle.net/1942/28409
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DC Field | Value | Language |
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dc.contributor.author | JOUCK, Toon | - |
dc.contributor.author | de Leoni, Massimiliano | - |
dc.contributor.author | DEPAIRE, Benoit | - |
dc.date.accessioned | 2019-06-14T08:23:48Z | - |
dc.date.available | 2019-06-14T08:23:48Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Daniel, Florian; Sheng, Quan Z.; Motahari, Hamid (Ed.). Business Process Management Workshops, Springer Inernational Publishing,p. 482-493 | - |
dc.identifier.isbn | 978-3-030-11641-5 | - |
dc.identifier.issn | 1865-1348 | - |
dc.identifier.uri | http://hdl.handle.net/1942/28409 | - |
dc.description.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. | - |
dc.language.iso | en | - |
dc.publisher | Springer Inernational Publishing | - |
dc.relation.ispartofseries | Lecture Notes in Business Information Processing | - |
dc.rights | Springer Nature Switzerland AG 2019 | - |
dc.subject.other | Decision mining; Evaluation; Log generation | - |
dc.title | A Framework to Evaluate and Compare Decision-Mining Techniques | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.authors | Daniel, Florian | - |
local.bibliographicCitation.authors | Sheng, Quan Z. | - |
local.bibliographicCitation.authors | Motahari, Hamid | - |
local.bibliographicCitation.conferencedate | 9 sep 2018 - 14 sep 2018 | - |
local.bibliographicCitation.conferencename | International Conference on Business Process Management | - |
local.bibliographicCitation.conferenceplace | Sydney, Australia | - |
dc.identifier.epage | 493 | - |
dc.identifier.spage | 482 | - |
local.bibliographicCitation.jcat | C1 | - |
local.publisher.place | Cham | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
local.relation.ispartofseriesnr | 342 | - |
dc.identifier.doi | 10.1007/978-3-030-11641-5_38 | - |
local.bibliographicCitation.btitle | Business Process Management Workshops | - |
item.fullcitation | JOUCK, Toon; de Leoni, Massimiliano & DEPAIRE, Benoit (2019) A Framework to Evaluate and Compare Decision-Mining Techniques. In: Daniel, Florian; Sheng, Quan Z.; Motahari, Hamid (Ed.). Business Process Management Workshops, Springer Inernational Publishing,p. 482-493. | - |
item.fulltext | With Fulltext | - |
item.validation | vabb 2021 | - |
item.contributor | JOUCK, Toon | - |
item.contributor | de Leoni, Massimiliano | - |
item.contributor | DEPAIRE, Benoit | - |
item.accessRights | Restricted Access | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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paper.pdf Restricted Access | Peer-reviewed author version | 413.51 kB | Adobe PDF | View/Open Request a copy |
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