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Predictive Monitoring of Business Processes

arXiv 1312.4874 ↗First posted 17 Dec 2013cs.SEcited by 37

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Abstract (arXiv)

Modern information systems that support complex business processes generally maintain significant amounts of process execution data, particularly records of events corresponding to the execution of activities (event logs). In this paper, we present an approach to analyze such event logs in order to predictively monitor business goals during business process execution. At any point during an execution of a process, the user can define business goals in the form of linear temporal logic rules. When an activity is being executed, the framework identifies input data values that are more (or less) likely to lead to the achievement of each business goal. Unlike reactive compliance monitoring approaches that detect violations only after they have occurred, our predictive monitoring approach provides early advice so that users can steer ongoing process executions towards the achievement of business goals. In other words, violations are predicted (and potentially prevented) rather than merely detected. The approach has been implemented in the ProM process mining toolset and validated on a real-life log pertaining to the treatment of cancer patients in a large hospital.

Key facts. Cited by 37 papers in the map (data through 13 Oct 2026). First posted on arXiv 17 Dec 2013.

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Citing papers per year: 2021: 8; 2022: 8; 2023: 7; 2024: 5; 2025: 8; 2026: 1.

37 papers.

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  1. 2021A systematic literature review on state-of-the-art deep learning methods for process predictioncited by 32
  2. 2021Prescriptive Process Monitoring: Quo Vadis?cited by 15
  3. 2021Embedding Graph Convolutional Networks in Recurrent Neural Networks for Predictive Monitoringcited by 12
  4. 2022Counterfactual Explanations for Predictive Business Process Monitoringcited by 12
  5. 2023An Assessment of ChatGPT on Log Datacited by 12
  6. 2021A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processescited by 11
  7. 2022When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraintscited by 11
  8. 2023Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspectivecited by 10
  9. 2021How do I update my model? On the resilience of Predictive Process Monitoring models to changecited by 7
  10. 2021Evaluating Predictive Business Process Monitoring Approaches on Small Event Logscited by 6
  11. 2021Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networkscited by 6
  12. 2022Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful Modelscited by 5
25 more
  1. 2024Machine learning in business process management: A systematic literature reviewcited by 5
  2. 2025Comprehensive Attribute Encoding and Dynamic LSTM HyperModels for Outcome Oriented Predictive Business Process Monitoringcited by 5
  3. 2022Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directionscited by 4
  4. 2023Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoringcited by 4
  5. 2025HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Datacited by 4
  6. 2022Explainable Predictive Process Monitoring: A User Evaluationcited by 3
  7. 2023Performance-Preserving Event Log Sampling for Predictive Monitoringcited by 3
  8. 2024Guiding the generation of counterfactual explanations through temporal background knowledge for Predictive Process Monitoringcited by 3
  9. 2022Explainable Artificial Intelligence for Improved Modeling of Processescited by 2
  10. 2023A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areascited by 2
  11. 2022Learning to act: a Reinforcement Learning approach to recommend the best next activitiescited by 1
  12. 2022Nirdizati: an Advanced Predictive Process Monitoring Toolkitcited by 1
  13. 2025Beyond Yes or No: Predictive Compliance Monitoring Approaches for Quantifying the Magnitude of Compliance Violationscited by 1
  14. 2025From Source to Target: Leveraging Transfer Learning for Predictive Process Monitoring in Organizationscited by 1
  15. 2025A Human-In-The-Loop Approach for Improving Fairness in Predictive Business Process Monitoringcited by 1
  16. 2021A Systematic Literature Review on Process-Aware Recommender Systemscited by 0
  17. 2023Explain, Adapt and Retrain: How to improve the accuracy of a PPM classifier through different explanation stylescited by 0
  18. 2023Inter-case Predictive Process Monitoring: A candidate for Quantum Machine Learning?cited by 0
  19. 2024Structural Positional Encoding for knowledge integration in transformer-based medical process monitoringcited by 0
  20. 2024A Review of AI and Machine Learning Contribution in Predictive Business Process Management (Process Enhancement and Process Improvement Approaches)cited by 0
  21. 2024Extending predictive process monitoring for collaborative processescited by 0
  22. 2025Leveraging Taxonomy Similarity for Next Activity Prediction in Patient Treatmentcited by 0
  23. 2025An Uncertainty-Aware ED-LSTM for Probabilistic Suffix Predictioncited by 0
  24. 2025FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoringcited by 0
  25. 2026GNN4PPM: Multi-Target Predictive Process Monitoring with Relational Graph Convolutional Networkscited by 0