Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/43358
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dc.contributor.authorPRADHAN, Shameer-
dc.date.accessioned2024-07-09T12:37:12Z-
dc.date.available2024-07-09T12:37:12Z-
dc.date.issued2023-
dc.date.submitted2024-07-02T19:20:17Z-
dc.identifier.citationvan der Werf , Jan Martijn E. M.; Cabanillas, Cristina; Leotta, Francesco; Genga, Laura (Ed.). ICPM-D 2023 ICPM Doctoral Consortium and Demo Track 2023,-
dc.identifier.urihttp://hdl.handle.net/1942/43358-
dc.description.abstractData extraction and event log building are crucial steps in process mining. To effectively utilize process mining algorithms, it is necessary to have process data available in a suitable event log format. However, the current process of extracting data and building event logs demands considerable time and effort. The objective of this Ph.D. research is to improve the support for process mining practitioners in extracting data from information systems and building event logs from the extracted data. Furthermore, we would like to facilitate interactive support with the minimum amount of input from the perspective of the process mining expert.-
dc.language.isoen-
dc.relation.ispartofseriesCEUR Workshop Proceedings-
dc.subject.otherProcess mining-
dc.subject.otherData extraction-
dc.subject.otherEvent log building-
dc.subject.otherData preparation-
dc.subject.otherRelational database-
dc.titleUser-Friendly Data Extraction and Event Log Building for Process Mining (Extended Abstract)-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsvan der Werf , Jan Martijn E. M.-
local.bibliographicCitation.authorsCabanillas, Cristina-
local.bibliographicCitation.authorsLeotta, Francesco-
local.bibliographicCitation.authorsGenga, Laura-
local.bibliographicCitation.conferencedate2023, October 23-27-
local.bibliographicCitation.conferencenameInternational Conference on Process Mining-
local.bibliographicCitation.conferenceplaceRome Italy-
dc.identifier.volume3648-
local.format.pages5-
local.bibliographicCitation.jcatC1-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper - Abstract-
local.relation.ispartofseriesnr3648-
local.provider.typePdf-
local.bibliographicCitation.btitleICPM-D 2023 ICPM Doctoral Consortium and Demo Track 2023-
local.uhasselt.internationalno-
item.fullcitationPRADHAN, Shameer (2023) User-Friendly Data Extraction and Event Log Building for Process Mining (Extended Abstract). In: van der Werf , Jan Martijn E. M.; Cabanillas, Cristina; Leotta, Francesco; Genga, Laura (Ed.). ICPM-D 2023 ICPM Doctoral Consortium and Demo Track 2023,.-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
item.contributorPRADHAN, Shameer-
crisitem.journal.issn1613-0073-
Appears in Collections:Research publications
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