SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Explainable Business Process Remaining Time Prediction Using Reachability Graph
16 references·0 citing·32 second hop
Explainable Business Process Remaining Time Prediction Using Reachability Graph (2023)Explainable Business Process Remaining Ti…Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction (2020)Predictive Business Process M…Explainable Predictive Process Monitoring (2020)Explainable Predictive Proces…Explainable predictive business process monitoring using gated graph neural networks (2020)Explainable predictive busine…Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring (2019)Survey and Cross-benchmark Co…Predicting performances in business processes using deep neural networks (2019)Predicting performances in bu…Outcome-Oriented Predictive Process Monitoring (2019)Outcome-Oriented Predictive P…Learning Accurate LSTM Models of Business Processes (2019)Learning Accurate LSTM Models…Decay Replay Mining to Predict Next Process Events (2019)Decay Replay Mining to Predic…Time and activity sequence prediction of business process instances (2018)Time and activity sequence pr…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…LSTM networks for data-aware remaining time prediction of business process instances (2017)LSTM networks for data-aware …Process Mining (2016)Process MiningDiscovering Block-Structured Process Models from Event Logs - A Constructive Approach (2013)Discovering Block-Structured …Time prediction based on process mining (2010)Time prediction based on proc…Cycle Time Prediction: When Will This Case Finally Be Finished? (2008)Cycle Time Prediction: When W…Workflow mining: A survey of issues and approaches (2003)Workflow mining: discovering process models from event logs (2004)Conformance checking of processes based on monitoring real behavior (2007)Process Mining (2012)Predictive Monitoring of Business Processes (2014)Predictive Monitoring of Business Processes: A Survey (2017)Genetic Process Mining (2005)Business process mining: An industrial application (2006)Genetic process mining: an experimental evaluation (2007)Beyond Process Mining: From the Past to Present and Future (2010)Prediction of Remaining Service Execution Time Using Stochastic Petri Nets with Arbitrary Firing Delays (2013)Using Convolutional Neural Networks for Predictive Process Analytics (2019)Process Mining (2011)Process Mining: Discovery, Conformance and Enhancement of Business Processes (2011)Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour (2014)Process mining in healthcare: A literature review (2016)Automated Discovery of Process Models from Event Logs: Review and Benchmark (2018)Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications (2000)Activity Prediction of Business Process Instances with Inception CNN Models (2019)Creating business value with process mining (2022)Predictive Process Monitoring (2022)Procedures for Performing Systematic Reviews (2004)Process Mining Manifesto (2012)Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction (2020)A systematic literature review on state-of-the-art deep learning methods for process prediction (2021)Another look at measures of forecast accuracy (2006)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)Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities (2020)
this work references cited by second hop

References

  • 2016Process Mining2,166 cited
  • 2013Discovering Block-Structured Process Models from Event Logs - A Constructive Approach648 cited
  • 2017Predictive Business Process Monitoring with LSTM Neural Networks554 cited
  • 2010Time prediction based on process mining507 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
  • 2018Predictive Process Monitoring Methods: Which One Suits Me Best?175 cited
  • 2018Time and activity sequence prediction of business process instances138 cited
  • 2008Cycle Time Prediction: When Will This Case Finally Be Finished?132 cited
  • 2017LSTM networks for data-aware remaining time prediction of business process instances118 cited
  • 2020Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction114 cited
  • 2020Explainable predictive business process monitoring using gated graph neural networks84 cited
  • 2020Explainable Predictive Process Monitoring81 cited
  • 2019Predicting performances in business processes using deep neural networks

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

75 cited
  • 2019Decay Replay Mining to Predict Next Process Events62 cited
  • Cited by

    No citing works inside the corpus for this window.