Towards Scalable Process Mining Pipelines

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dc.contributor.authorMohamed, Belal
dc.contributor.authorElHelw, Mohamed
dc.contributor.authorAwad, Ahmed
dc.date.accessioned2025-05-06T10:12:00Z
dc.date.available2025-05-06T10:12:00Z
dc.date.issued2023
dc.description.abstractOver the past two decades, process mining has proven to be a valuable approach to gain insights into or ganizations’ performance. The major sub-fields of discovery, conformance, and improvement have witnessed substantial de velopment. Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. Mostly, these contributions were addressing process mining guidelines from the process mining manifesto. In this paper, we address the sixth guideline in the process mining manifesto. That is, process mining should be a continuous process. For this, we propose a pipelining approach that is: configurable, scalable, modular, and automated. We realize our proposal using Dask and evaluate it with different architectures, process discovery, and evaluation metrics.
dc.identifier.citationAwad, A. et al. (2023) “Towards Scalable Process Mining Pipelines,” in 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), pp. 125–182.
dc.identifier.doihttps://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361330.
dc.identifier.issnElectronic ISSN: 2837-0740 Print on Demand(PoD) ISSN: 2837-0724
dc.identifier.urihttps://bspace.buid.ac.ae/handle/1234/2937
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofseries2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) also in125-182
dc.subjectMeasurement,Organizations,Computer architecture,Big Data,Data mining,Proposals,Pipeline processing
dc.titleTowards Scalable Process Mining Pipelines
dc.typeArticle
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Dr Ahmed Awad