Towards Scalable Process Mining Pipelines

Mohamed, Belal; ElHelw, Mohamed; Awad, Ahmed

Towards Scalable Process Mining Pipelines

Date

2023

Authors

Mohamed, Belal

ElHelw, Mohamed

Awad, Ahmed

Publisher

IEEE

Abstract

Over 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.

Keywords

Measurement,Organizations,Computer architecture,Big Data,Data mining,Proposals,Pipeline processing

Citation

Awad, 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.