mlsanityData to 14 Oct 2026

Probability Estimation of Uncertain Process Trace Realizations

arXiv 2108.08615 ↗First posted 19 Aug 2021cs.AIcited by 6

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Abstract (arXiv)

Process mining is a scientific discipline that analyzes event data, often collected in databases called event logs. Recently, uncertain event logs have become of interest, which contain non-deterministic and stochastic event attributes that may represent many possible real-life scenarios. In this paper, we present a method to reliably estimate the probability of each of such scenarios, allowing their analysis. Experiments show that the probabilities calculated with our method closely match the true chances of occurrence of specific outcomes, enabling more trustworthy analyses on uncertain data.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 19 Aug 2021.

Builds on

5 of 11 references.

References · 5

  1. 2019Process Mining for Python (PM4Py): Bridging the Gap Between Process- and Data Sciencecited by 33
  2. 2020Conformance Checking over Uncertain Event Datacited by 13
  3. 2019Mining Uncertain Event Data in Process Miningcited by 9
  4. 2019Discovering Process Models from Uncertain Event Datacited by 8
  5. 2020Partial Order Resolution of Event Logs for Process Conformance Checkingcited by 3

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Cited by year

Citing papers per year: 2022: 5; 2023: 0; 2024: 1.

6 papers.