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http://hdl.handle.net/1942/43358
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DC Field | Value | Language |
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dc.contributor.author | PRADHAN, Shameer | - |
dc.date.accessioned | 2024-07-09T12:37:12Z | - |
dc.date.available | 2024-07-09T12:37:12Z | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2024-07-02T19:20:17Z | - |
dc.identifier.citation | van 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.uri | http://hdl.handle.net/1942/43358 | - |
dc.description.abstract | Data 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.iso | en | - |
dc.relation.ispartofseries | CEUR Workshop Proceedings | - |
dc.subject.other | Process mining | - |
dc.subject.other | Data extraction | - |
dc.subject.other | Event log building | - |
dc.subject.other | Data preparation | - |
dc.subject.other | Relational database | - |
dc.title | User-Friendly Data Extraction and Event Log Building for Process Mining (Extended Abstract) | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.authors | van der Werf , Jan Martijn E. M. | - |
local.bibliographicCitation.authors | Cabanillas, Cristina | - |
local.bibliographicCitation.authors | Leotta, Francesco | - |
local.bibliographicCitation.authors | Genga, Laura | - |
local.bibliographicCitation.conferencedate | 2023, October 23-27 | - |
local.bibliographicCitation.conferencename | International Conference on Process Mining | - |
local.bibliographicCitation.conferenceplace | Rome Italy | - |
dc.identifier.volume | 3648 | - |
local.format.pages | 5 | - |
local.bibliographicCitation.jcat | C1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper - Abstract | - |
local.relation.ispartofseriesnr | 3648 | - |
local.provider.type | - | |
local.bibliographicCitation.btitle | ICPM-D 2023 ICPM Doctoral Consortium and Demo Track 2023 | - |
local.uhasselt.international | no | - |
item.fullcitation | PRADHAN, 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.accessRights | Open Access | - |
item.fulltext | With Fulltext | - |
item.contributor | PRADHAN, Shameer | - |
crisitem.journal.issn | 1613-0073 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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User_Friendly_Data_Extraction_and_Event_Log_Building_for_Process_Mining__Extended_Abstract.pdf | Published version | 151.38 kB | Adobe PDF | View/Open |
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