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http://hdl.handle.net/1942/30239
Title: | Interactive Data Cleaning for Process Mining: A Case Study of an Outpatient Clinic’s Appointment System | Authors: | MARTIN, Niels Martinez-Millana, Antonio Valdivieso, Bernardo Fernández-Llatas, Carlos |
Issue Date: | 2019 | Publisher: | Springer, Cham | Source: | Di Francescomarino, Chiara; Dijkman, Remco; Zdun, Uwe (ed.). Business Process Management Workshops BPM 2019 International Workshops, Vienna, Austria, September 1–6, 2019, Revised Selected Papers. Springer, Cham, p. 532 -544 | Series/Report: | Lecture Notes in Business Information Processing | Series/Report no.: | 362 | Abstract: | Hospitals are becoming increasingly aware of the need to improve their processes and data-driven approaches, such as process mining, are gaining attention. When applying process mining techniques in reality , it is widely recognized that real-life data tends to suffer from data quality problems. Consequently, thorough data quality assessment and data cleaning is required. This paper proposes an interactive data cleaning approach for process mining. It encompasses both data-based and discovery-based data quality assessment, showing that both are complementary. To illustrate some key elements of the proposed approach, a case study of an outpatient clinic's appointment system is considered. | Keywords: | Process mining;Data quality;Interactive data cleaning;Process discovery;Outpatient clinic | Document URI: | http://hdl.handle.net/1942/30239 | ISBN: | 9783030374525 9783030374532 |
DOI: | 10.1007/978-3-030-37453-2_43 | ISI #: | 000723926800056 | Rights: | 2019 Springer Nature Switzerland AG. Part of Springer Nature. | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2022 vabb 2021 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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Manuscript document server.pdf | Peer-reviewed author version | 372.53 kB | Adobe PDF | View/Open |
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