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http://hdl.handle.net/1942/43358
Title: | User-Friendly Data Extraction and Event Log Building for Process Mining (Extended Abstract) | Authors: | PRADHAN, Shameer | Issue Date: | 2023 | Source: | van der Werf , Jan Martijn E. M.; Cabanillas, Cristina; Leotta, Francesco; Genga, Laura (Ed.). ICPM-D 2023 ICPM Doctoral Consortium and Demo Track 2023, | Series/Report: | CEUR Workshop Proceedings | Series/Report no.: | 3648 | 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. | Keywords: | Process mining;Data extraction;Event log building;Data preparation;Relational database | Document URI: | http://hdl.handle.net/1942/43358 | ISSN: | 1613-0073 | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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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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