Predictive Process Monitoring
22 papers with code • 0 benchmarks • 1 datasets
A branch of predictive analysis that attempts to predict some future state of a business process.
Benchmarks
These leaderboards are used to track progress in Predictive Process Monitoring
Ultra-processed Food Dataset
Most implemented papers
Explainability of Predictive Process Monitoring Results: Can You See My Data Issues?
To address this gap, we investigate the effect of different PPM settings on resulting data fed into an ML model and consequently to a XAI method.
XAI in the context of Predictive Process Monitoring: Too much to Reveal
To address this gap, we provide a framework to enable studying the effect of different PPM-related settings and ML model-related choices on characteristics and expressiveness of resulting explanations.
Can deep neural networks learn process model structure? An assessment framework and analysis
Therefore, in this work, we propose an evaluation scheme complemented with new fitness, precision, and generalisation metrics, specifically tailored towards measuring the capacity of deep learning models to learn process model structure.
Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful Models
In this paper, we define explainability through the interpretability of the explanations and the faithfulness of the explainability model in the field of process outcome prediction.
Learning Uncertainty with Artificial Neural Networks for Improved Predictive Process Monitoring
The inability of artificial neural networks to assess the uncertainty of their predictions is an impediment to their widespread use.
Can recurrent neural networks learn process model structure?
In this work, we investigate the capabilities of such an LSTM to actually learn the underlying process model structure of an event log.
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.
Measuring the Stability of Process Outcome Predictions in Online Settings
This paper proposes an evaluation framework for assessing the stability of models for online predictive process monitoring.
Knowledge-Driven Modulation of Neural Networks with Attention Mechanism for Next Activity Prediction
Predictive Process Monitoring (PPM) aims at leveraging historic process execution data to predict how ongoing executions will continue up to their completion.
