{"total":43,"rows":[{"id":"2101.09320","title":"A systematic literature review on state-of-the-art deep learning methods for process prediction","created":"2021-01-22","cited_by_count":32,"area":null},{"id":"2105.07111","title":"Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction","created":"2021-05-15","cited_by_count":17,"area":null},{"id":"2107.01905","title":"Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring","created":"2021-07-05","cited_by_count":16,"area":null},{"id":"2404.06267","title":"PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances","created":"2024-04-09","cited_by_count":14,"area":null},{"id":"2107.08697","title":"DiCE4EL: Interpreting Process Predictions using a Milestone-Aware Counterfactual Approach","created":"2021-07-19","cited_by_count":13,"area":null},{"id":"2202.12018","title":"Counterfactual Explanations for Predictive Business Process Monitoring","created":"2022-02-24","cited_by_count":12,"area":null},{"id":"2309.07938","title":"An Assessment of ChatGPT on Log Data","created":"2023-09-14","cited_by_count":12,"area":null},{"id":"2206.07745","title":"When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints","created":"2022-06-15","cited_by_count":11,"area":null},{"id":"2304.06412","title":"Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective","created":"2023-04-13","cited_by_count":10,"area":null},{"id":"2104.00362","title":"Evaluating Predictive Business Process Monitoring Approaches on Small Event Logs","created":"2021-04-01","cited_by_count":6,"area":null},{"id":"2109.01419","title":"Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms","created":"2021-09-03","cited_by_count":6,"area":null},{"id":"2203.02801","title":"Object-centric Process Predictive Analytics","created":"2022-03-05","cited_by_count":6,"area":null},{"id":"2205.05446","title":"Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directions","created":"2022-05-10","cited_by_count":5,"area":null},{"id":"2405.16396","title":"Machine learning in business process management: A systematic literature review","created":"2024-05-26","cited_by_count":5,"area":null},{"id":"2412.04914","title":"Achieving Group Fairness through Independence in Predictive Process Monitoring","created":"2024-12-06","cited_by_count":5,"area":null},{"id":"2506.03696","title":"Comprehensive Attribute Encoding and Dynamic LSTM HyperModels for Outcome Oriented Predictive Business Process Monitoring","created":"2025-06-04","cited_by_count":5,"area":null},{"id":"2105.05559","title":"Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes","created":"2021-05-12","cited_by_count":4,"area":null},{"id":"2307.05939","title":"Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoring","created":"2023-07-12","cited_by_count":4,"area":null},{"id":"2202.07760","title":"Explainable Predictive Process Monitoring: A User Evaluation","created":"2022-02-15","cited_by_count":3,"area":null},{"id":"2206.06317","title":"Learning Uncertainty with Artificial Neural Networks for Improved Predictive Process Monitoring","created":"2022-06-13","cited_by_count":3,"area":null},{"id":"2207.10017","title":"Predictive Object-Centric Process Monitoring","created":"2022-07-20","cited_by_count":3,"area":null},{"id":"2301.07624","title":"Performance-Preserving Event Log Sampling for Predictive Monitoring","created":"2023-01-18","cited_by_count":3,"area":null},{"id":"2107.09767","title":"Explainable AI Enabled Inspection of Business Process Prediction Models","created":"2021-07-16","cited_by_count":2,"area":null},{"id":"2302.04018","title":"A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas","created":"2023-02-08","cited_by_count":2,"area":null},{"id":"2406.01786","title":"Recent Advances in Data-Driven Business Process Management","created":"2024-06-03","cited_by_count":2,"area":null},{"id":"2508.09527","title":"Time-Aware and Transition-Semantic Graph Neural Networks for Interpretable Predictive Business Process Monitoring","created":"2025-08-13","cited_by_count":2,"area":null},{"id":"2509.00797","title":"ProCause: Generating Counterfactual Outcomes to Evaluate Prescriptive Process Monitoring Methods","created":"2025-08-31","cited_by_count":2,"area":null},{"id":"2105.01092","title":"Process Model Forecasting Using Time Series Analysis of Event Sequence Data","created":"2021-05-03","cited_by_count":1,"area":null},{"id":"2202.08265","title":"XAI in the context of Predictive Process Monitoring: Too much to Reveal","created":"2022-02-16","cited_by_count":1,"area":null},{"id":"2206.13109","title":"Enhancing Stochastic Petri Net-based Remaining Time Prediction using k-Nearest Neighbors","created":"2022-06-27","cited_by_count":1,"area":null},{"id":"2210.09688","title":"Nirdizati: an Advanced Predictive Process Monitoring Toolkit","created":"2022-10-18","cited_by_count":1,"area":null},{"id":"2312.05560","title":"Enhancing the Accuracy of Predictors of Activity Sequences of Business Processes","created":"2023-12-09","cited_by_count":1,"area":null},{"id":"2503.07683","title":"Log Optimization Simplification Method for Predicting Remaining Time","created":"2025-03-10","cited_by_count":1,"area":null},{"id":"2508.08061","title":"From Source to Target: Leveraging Transfer Learning for Predictive Process Monitoring in Organizations","created":"2025-08-11","cited_by_count":1,"area":null},{"id":"2508.17477","title":"A Human-In-The-Loop Approach for Improving Fairness in Predictive Business Process Monitoring","created":"2025-08-24","cited_by_count":1,"area":null},{"id":"2103.16654","title":"A Systematic Literature Review on Process-Aware Recommender Systems","created":"2021-03-30","cited_by_count":0,"area":null},{"id":"2303.14939","title":"Explain, Adapt and Retrain: How to improve the accuracy of a PPM classifier through different explanation styles","created":"2023-03-27","cited_by_count":0,"area":null},{"id":"2407.17881","title":"Unraveling the Never-Ending Story of Lifecycles and Vitalizing Processes","created":"2024-07-25","cited_by_count":0,"area":null},{"id":"2505.21339","title":"An Uncertainty-Aware ED-LSTM for Probabilistic Suffix Prediction","created":"2025-05-27","cited_by_count":0,"area":null},{"id":"2506.16617","title":"The Role of Explanation Styles and Perceived Accuracy on Decision Making in Predictive Process Monitoring","created":"2025-06-19","cited_by_count":0,"area":null},{"id":"2509.14536","title":"How Will My Business Process Unfold? Predicting Case Suffixes With Start and End Timestamps","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2512.17629","title":"SCOPE: Sequential Causal Optimization of Process Interventions","created":"2025-12-19","cited_by_count":0,"area":null},{"id":"2601.11468","title":"Exploring LLM Features in Predictive Process Monitoring for Small-Scale Event-Logs","created":"2026-01-16","cited_by_count":0,"area":null}],"next_cursor":null}