process mining, i.e., a sub-field of datascience focusing on the analysis of event data generated during the execution of (business) processes, has seen a tremendous change over the past two decades. Starting off in ...
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process mining, i.e., a sub-field of datascience focusing on the analysis of event data generated during the execution of (business) processes, has seen a tremendous change over the past two decades. Starting off in ...
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We show that conducting a process-mining-centric analysis concerning cyber-physical systems provides insights into usage behavior. To show that, we perform our analysis on connected-vehicle data. We transform connecte...
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In business processes, the behavior, evolution and interactions of objects influence the outcome of process instances, and thus the value that a business user may assign to them. For example, in an order-to-cash proce...
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process mining is a technology that helps understand, analyze, and improve processes. It has been present for around two decades, and although initially tailored for business processes, the spectrum of analyzed p...
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Calibrating camera networks is a complex yet crucial task for ensuring accurate data collection, particularly for large-scale scenarios. This work's main contribution is a method for efficiently estimating the net...
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data interoperability in Industry 4.0 is a continuous challenge for industry and research. Many organizations face the challenge of managing data lakes that, without proper governance, risk becoming disorganized ‘dat...
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SLURMminer is a tool designed to analyze SLURM systems in High-Performance Computing (HPC) clusters. It utilizes process mining techniques to generate event logs, extract process models, and visualize critical busines...
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Fairness in process mining is vital for data-based decisions, but progress is hampered by limited event data accounting for fairness. We're offering a set of simulated event logs covering four key areas, showcasin...
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