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Analysing the Foraging Behaviour of Bees Using Process Mining: A Case Study Kapitel lesen Erstes Kapitel lesen

2024 | OriginalPaper | Buchkapitel

Turning Logs into Lumber: Preprocessing Tasks in Process Mining

verfasst von : Ying Liu, Vinicius Stein Dani, Iris Beerepoot, Xixi Lu

Erschienen in: Process Mining Workshops

Verlag: Springer Nature Switzerland

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Abstract

Event logs are invaluable for conducting process mining projects, offering insights into process improvement and data-driven decision-making. However, data quality issues affect the correctness and trustworthiness of these insights, making preprocessing tasks a necessity. Despite the recognized importance, the execution of preprocessing tasks remains ad-hoc, lacking support. This paper presents a systematic literature review that establishes a comprehensive repository of preprocessing tasks and their usage in case studies. We identify six high-level and 20 low-level preprocessing tasks in case studies. Log filtering, transformation, and abstraction are commonly used, while log enriching, integration, and reduction are less frequent. These results can be considered a first step in contributing to more structured, transparent event log preprocessing, enhancing process mining reliability.

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Vorheriges Kapitel Event Knowledge Graphs for Auditing: A Case Study
Nächstes Kapitel Improving Precision in Process Trees Using Subprocess Tree Logs
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Metadaten
Titel
Turning Logs into Lumber: Preprocessing Tasks in Process Mining
verfasst von
Ying Liu
Vinicius Stein Dani
Iris Beerepoot
Xixi Lu
Copyright-Jahr
2024
Buch
Process Mining Workshops

Print ISBN: 978-3-031-56106-1

Electronic ISBN: 978-3-031-56107-8

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-3-031-56107-8_8

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