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Found 5 papers, 3 papers with code
Tailoring Machine Learning for Process Mining
Machine learning models are routinely integrated into process mining pipelines to carry out tasks like data transformation, noise reduction, anomaly detection, classification, and prediction.
CoSMo: a Framework to Instantiate Conditioned Process Simulation Models
This architecture facilitates the simulation of event logs that adhere to specific constraints by incorporating declarative-based rules into the learning phase as an attempt to fill the gap of incorporating information into deep learning models to perform what-if analysis.
Trace Encoding in Process Mining: a survey and benchmarking
Encoding methods are employed across several process mining tasks, including predictive process monitoring, anomalous case detection, trace clustering, etc.
Selecting Optimal Trace Clustering Pipelines with AutoML
Trace clustering has been extensively used to preprocess event logs.
Using Meta-learning to Recommend Process Discovery Methods
Process discovery methods have obtained remarkable achievements in Process Mining, delivering comprehensible process models to enhance management capabilities.
