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Approaches for IoT-enhanced predictive process monitoring
16 references·0 citing·32 second hop
Approaches for IoT-enhanced predictive process monitoring (2025)Approaches for IoT-enhanced predictive pr…Process Mining: A 360 Degree Overview (2022)Process Mining: A 360 Degree …Predictive Process Monitoring (2022)Predictive Process MonitoringTowards IoT-driven Process Event Log Generation for Conformance Checking in Smart Factories (2020)Towards IoT-driven Process Ev…The Internet of Things Meets Business Process Management: A Manifesto (2020)The Internet of Things Meets …Outcome-Oriented Predictive Process Monitoring (2019)Outcome-Oriented Predictive P…Learning Accurate LSTM Models of Business Processes (2019)Learning Accurate LSTM Models…From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring (2019)From knowledge-driven to data…Predictive Process Monitoring Methods: Which One Suits Me Best? (2018)Predictive Process Monitoring…Predictive Business Process Monitoring with LSTM Neural Networks (2017)Predictive Business Process M…Predicting process behaviour using deep learning (2017)Predicting process behaviour …Intra and Inter-case Features in Predictive Process Monitoring: A Tale of Two Dimensions (2017)Intra and Inter-case Features…A Multi-stage Deep Learning Approach for Business Process Event Prediction (2017)A Multi-stage Deep Learning A…Predictive Business Process Monitoring with Structured and Unstructured Data (2016)Predictive Business Process M…Enabling process mining on sensor data from smart products (2016)Enabling process mining on se…Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes (2015)Complex Symbolic Sequence Enc…A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs (2015)A general process mining fram…Time prediction based on process mining (2010)Predictive Monitoring of Business Processes (2014)Clustering-Based Predictive Process Monitoring (2016)Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction (2020)Flexible Heuristics Miner (FHM) (2011)Replaying history on process models for conformance checking and performance analysis (2012)Decision support from financial disclosures with deep neural networks and transfer learning (2017)Process mining techniques and applications – A systematic mapping study (2019)Procedures for Performing Systematic Reviews (2004)Process Mining Manifesto (2012)Process Mining (2016)A systematic literature review on state-of-the-art deep learning methods for process prediction (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)Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction (2020)A model for types and levels of human interaction with automation (2000)Discrimination-aware data mining (2008)Modelling and executing IoT-enhanced business processes through BPMN and microservices (2021)Process Prediction with Digital Twins (2021)The Principles of Scientific Management. (1912)Workflow mining: discovering process models from event logs (2004)Foundations of Process Discovery (2022)Process Mining over Multiple Behavioral Dimensions with Event Knowledge Graphs (2022)Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective (2024)The ProM Framework: A New Era in Process Mining Tool Support (2005)Foundations of Process Event Data (2022)A review of AI and machine learning contribution in business process management (process enhancement and process improvement approaches) (2024)Predictive process monitoring: concepts, challenges, and future research directions (2024)Discovering Block-Structured Process Models from Event Logs - A Constructive Approach (2013)Fundamentals of Business Process Management (2013)Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring (2019)
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References

  • 2017Predictive Business Process Monitoring with LSTM Neural Networks554 cited
  • 2017Predicting process behaviour using deep learning430 cited
  • 2019Outcome-Oriented Predictive Process Monitoring352 cited
  • 2015A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs251 cited
  • 2019Learning Accurate LSTM Models of Business Processes241 cited
  • 2015Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes191 cited
  • 2022Process Mining: A 360 Degree Overview179 cited
  • 2020The Internet of Things Meets Business Process Management: A Manifesto177 cited
  • 2018Predictive Process Monitoring Methods: Which One Suits Me Best?175 cited
  • 2022Predictive Process Monitoring129 cited
  • 2016Predictive Business Process Monitoring with Structured and Unstructured Data108 cited
  • 2017Intra and Inter-case Features in Predictive Process Monitoring: A Tale of Two Dimensions105 cited
  • 2016Enabling process mining on sensor data from smart products78 cited
  • 2017A Multi-stage Deep Learning Approach for Business Process Event Prediction63 cited
  • 2019From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring

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59 cited
  • 2020Towards IoT-driven Process Event Log Generation for Conformance Checking in Smart Factories49 cited
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