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Enhancing Predictive Process Monitoring with Time-Related Feature Engineering
16 references·0 citing·34 second hop
Enhancing Predictive Process Monitoring with Time-Related Feature Engineering (2024)Enhancing Predictive Process Monitoring w…Trace encoding in process mining: A survey and benchmarking (2023)Trace encoding in process min…Deep Learning for Predictive Business Process Monitoring: Review and Benchmark (2023)Deep Learning for Predictive …An explainable decision support system for predictive process analytics (2023)An explainable decision suppo…Learning Accurate Business Process Simulation Models from Event Logs via Automated Process Discovery and Deep Learning (2022)Learning Accurate Business Pr…Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring (2022)Creating Unbiased Public Benc…Encoding resource experience for predictive process monitoring (2021)Encoding resource experience …Explainability in Predictive Process Monitoring: When Understanding Helps Improving (2020)Explainability in Predictive …Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring (2019)Survey and Cross-benchmark Co…Outcome-Oriented Predictive Process Monitoring (2019)Outcome-Oriented Predictive P…Learning Accurate LSTM Models of Business Processes (2019)Learning Accurate LSTM Models…Data Management Challenges for Deep Learning (2019)Data Management Challenges fo…Time and activity sequence prediction of business process instances (2018)Time and activity sequence pr…Predictive Business Process Monitoring with LSTM Neural Networks (2017)Predictive Business Process M…LSTM networks for data-aware remaining time prediction of business process instances (2017)LSTM networks for data-aware …Intra and Inter-case Features in Predictive Process Monitoring: A Tale of Two Dimensions (2017)Intra and Inter-case Features…Process Mining (2016)Process MiningQueueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications (2000)Process Mining (2011)Process Mining: Discovery, Conformance and Enhancement of Business Processes (2011)Activity Prediction of Business Process Instances with Inception CNN Models (2019)Creating business value with process mining (2022)Predictive Process Monitoring (2022)Time prediction based on process mining (2010)A Novel Business Process Prediction Model Using a Deep Learning Method (2018)From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring (2019)A Multi-View Deep Learning Approach for Predictive Business Process Monitoring (2021)Reengineering the corporation: A manifesto for business revolution (1993)Explainable predictive business process monitoring using gated graph neural networks (2020)Explainable Predictive Process Monitoring (2020)Procedures for Performing Systematic Reviews (2004)Another look at measures of forecast accuracy (2006)Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction (2020)A systematic literature review on state-of-the-art deep learning methods for process prediction (2021)Business process variant analysis: Survey and classification (2021)Fundamentals of Business Process Management (2018)The biggest business process management problems to solve before we die (2023)Towards comprehensive support for organizational mining (2008)Predicting process behaviour using deep learning (2017)Deep learning applications and challenges in big data analytics (2015)Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers (2015)Doing a thematic analysis: A practical, step-by-step guide for learning and teaching scholars. (2017)Data Pipeline Management in Practice: Challenges and Opportunities (2020)Open Data Ecosystems — An empirical investigation into an emerging industry collaboration concept (2021)An XGBoost-Based Three-Stage Prediction Approach for True User Demand of Bike-Sharing Systems Based on Spatio-Temporal Analysis (2025)Measurement Reliability and Validity (2000)A Systematic Review of Anomaly Detection for Business Process Event Logs (2023)Embedding Graph Convolutional Networks in Recurrent Neural Networks for Predictive Monitoring (2023)Machine learning in business process management: A systematic literature review (2024)Automated Discovery of Process Models from Event Logs: Review and Benchmark (2018)Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities (2020)
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References

  • 2016Process Mining2,166 cited
  • 2017Predictive Business Process Monitoring with LSTM Neural Networks554 cited
  • 2019Outcome-Oriented Predictive Process Monitoring352 cited
  • 2019Learning Accurate LSTM Models of Business Processes241 cited
  • 2019Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring207 cited
  • 2018Time and activity sequence prediction of business process instances138 cited
  • 2019Data Management Challenges for Deep Learning130 cited
  • 2017LSTM networks for data-aware remaining time prediction of business process instances118 cited
  • 2017Intra and Inter-case Features in Predictive Process Monitoring: A Tale of Two Dimensions105 cited
  • 2023Deep Learning for Predictive Business Process Monitoring: Review and Benchmark104 cited
  • 2020Explainability in Predictive Process Monitoring: When Understanding Helps Improving60 cited
  • 2023An explainable decision support system for predictive process analytics53 cited
  • 2023Trace encoding in process mining: A survey and benchmarking46 cited
  • 2022Learning Accurate Business Process Simulation Models from Event Logs via Automated Process Discovery and Deep Learning45 cited
  • 2021

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Encoding resource experience for predictive process monitoring
44 cited
  • 2022Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring34 cited
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