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http://hdl.handle.net/1942/36500
Title: | DaQAPO: Supporting flexible and fine-grained event log quality assessment | Authors: | MARTIN, Niels VAN HOUDT, Greg JANSSENSWILLEN, Gert |
Issue Date: | 2022 | Publisher: | PERGAMON-ELSEVIER SCIENCE LTD | Source: | Expert systems with applications, 191 (Art N° 116274) | Abstract: | Process mining can provide valuable insights in business processes using an event log containing process execution data. Despite the significant potential of process mining to support the analysis and improvement of processes, the reliability of process mining outcomes depends on the quality of the event log. Real-life logs typically suffer from various data quality issues. Consequently, thorough event log quality assessment is required before applying process mining algorithms. This paper introduces DaQAPO, the first R-package which supports flexible and fine-grained event log quality assessment. It provides a rich set of tests to identify a wide range of event log quality issues, while having sufficient flexibility to allow the detection of context-specific quality issues. | Keywords: | Process mining;Event log quality assessment;Event log quality;Data quality;Event log;R | Document URI: | http://hdl.handle.net/1942/36500 | ISSN: | 0957-4174 | e-ISSN: | 1873-6793 | DOI: | 10.1016/j.eswa.2021.116274 | ISI #: | 000744171700001 | Rights: | 2021 Elsevier Ltd. All rights reserved. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2023 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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1-s2.0-S0957417421015827-main.pdf Restricted Access | Published version | 1.86 MB | Adobe PDF | View/Open Request a copy |
Manuscript - Accepted version document server.pdf | Peer-reviewed author version | 423.43 kB | Adobe PDF | View/Open |
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