mlsanityData to 7 Oct 2026

Explainable Predictive Process Monitoring

arXiv 2008.01807 ↗First posted 4 Aug 2020cs.LG stat.MLcited by 27

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Abstract (arXiv)

Predictive Business Process Monitoring is becoming an essential aid for organizations, providing online operational support of their processes. This paper tackles the fundamental problem of equipping predictive business process monitoring with explanation capabilities, so that not only the what but also the why is reported when predicting generic KPIs like remaining time, or activity execution. We use the game theory of Shapley Values to obtain robust explanations of the predictions. The approach has been implemented and tested on real-life benchmarks, showing for the first time how explanations can be given in the field of predictive business process monitoring.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 12; 2023: 5; 2024: 4; 2025: 1; 2026: 3.

27 papers.

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  1. 2023Just Tell Me: Prompt Engineering in Business Process Managementcited by 17
  2. 2022Counterfactual Explanations for Predictive Business Process Monitoringcited by 12
  3. 2022An Explainable Decision Support System for Predictive Process Analyticscited by 8
  4. 2024How well can a large language model explain business processes as perceived by users?cited by 8
  5. 2021Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanismscited by 6
  6. 2022Object-centric Process Predictive Analyticscited by 6
  7. 2022Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestrationcited by 6
  8. 2022Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful Modelscited by 5
  9. 2024Machine learning in business process management: A systematic literature reviewcited by 5
  10. 2024Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)cited by 5
  11. 2025Self-Explaining Neural Networks for Business Process Monitoringcited by 5
  12. 2022Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directionscited by 4
15 more
  1. 2021The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directionscited by 3
  2. 2022Explainable Predictive Process Monitoring: A User Evaluationcited by 3
  3. 2022Explainability of Predictive Process Monitoring Results: Can You See My Data Issues?cited by 3
  4. 2022A Framework for Extracting and Encoding Features from Object-Centric Event Datacited by 3
  5. 2023Performance-Preserving Event Log Sampling for Predictive Monitoringcited by 3
  6. 2023Interpretable and Explainable Machine Learning Methods for Predictive Process Monitoring: A Systematic Literature Reviewcited by 3
  7. 2022Multi-Fault Diagnosis Of Industrial Rotating Machines Using Data-Driven Approach: A Review Of Two Decades Of Researchcited by 2
  8. 2023A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areascited by 2
  9. 2022XAI in the context of Predictive Process Monitoring: Too much to Revealcited by 1
  10. 2024A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsiscited by 1
  11. 2022Mining Explainable Predictive Features for Water Quality Managementcited by 0
  12. 2023Explain, Adapt and Retrain: How to improve the accuracy of a PPM classifier through different explanation stylescited by 0
  13. 2026Exploring LLM Features in Predictive Process Monitoring for Small-Scale Event-Logscited by 0
  14. 2026From Data Lifting to Continuous Risk Estimation: A Process-Aware Pipeline for Predictive Monitoring of Clinical Pathwayscited by 0
  15. 2026Feature Attribution-Based Explainability Analysis of Deep Learning Models in Predictive Process Monitoringcited by 0