Filtering and Sampling Object-Centric Event Logs
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Abstract (arXiv)
The scalability of process mining techniques is one of the main challenges to tackling the massive amount of event data produced every day in enterprise information systems. To this purpose, filtering and sampling techniques are proposed to keep a subset of the behavior of the original log and make the application of process mining techniques feasible. While techniques for filtering/sampling traditional event logs have been already proposed, filtering/sampling object-centric event logs is more challenging as the number of factors (events, objects, object types) to consider is significantly higher. This paper provides some techniques to filter/sample object-centric event logs.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 May 2022.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.
2 papers.
- 2022Clustering Object-Centric Event Logscited by 2
- 2024Extracting Process-Aware Decision Models from Object-Centric Process Datacited by 1
- 2024Extracting Process-Aware Decision Models from Object-Centric Process Data26 Jan 2024
- 2022Clustering Object-Centric Event Logs26 Jul 2022