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Discovering Context-Aware Models for Predicting Business Process Performances
8 references·16 citing·37 second hop
Discovering Context-Aware Models for Predicting Business Process Performances (2012)Discovering Context-Aware Models for Pred…Time prediction based on process mining (2010)Time prediction based on proc…Trace Clustering in Process Mining (2009)Trace Clustering in Process M…Supporting Flexible Processes through Recommendations Based on History (2008)Supporting Flexible Processes…Cycle Time Prediction: When Will This Case Finally Be Finished? (2008)Cycle Time Prediction: When W…Business Process Management Workshops (2008)Business Process Management W…ProM 4.0: Comprehensive Support for Real Process Analysis (2007)ProM 4.0: Comprehensive Suppo…Discovering expressive process models by clustering log traces (2006)Discovering expressive proces…Workflow mining: A survey of issues and approaches (2003)Workflow mining: A survey of …Explainability in Predictive Process Monitoring: When Understanding Helps Improving (2020)Explainability in Predictive …An extended model for remaining time prediction in manufacturing systems using process mining (2020)An extended model for remaini…Prediction-based Resource Allocation using LSTM and Minimum Cost and Maximum Flow Algorithm (2019)Prediction-based Resource All…From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring (2019)From knowledge-driven to data…Genetic algorithms for hyperparameter optimization in predictive business process monitoring (2018)Genetic algorithms for hyperp…A Novel Business Process Prediction Model Using a Deep Learning Method (2018)A Novel Business Process Pred…Run-time prediction of business process indicators using evolutionary decision rules (2017)Run-time prediction of busine…Intra and Inter-case Features in Predictive Process Monitoring: A Tale of Two Dimensions (2017)Intra and Inter-case Features…From event streams to process models and back: Challenges and opportunities (2017)From event streams to process…A Multi-stage Deep Learning Approach for Business Process Event Prediction (2017)A Multi-stage Deep Learning A…A Deep Learning Approach for Predicting Process Behaviour at Runtime (2017)A Deep Learning Approach for …Predictive Business Process Monitoring with Structured and Unstructured Data (2016)Predictive Business Process M…Queue Mining – Predicting Delays in Service Processes (2014)Queue Mining – Predicting Del…Data-aware remaining time prediction of business process instances (2014)Data-aware remaining time pre…A General Framework for Correlating Business Process Characteristics (2014)A General Framework for Corre…Supporting Risk-Informed Decisions during Business Process Execution (2013)Supporting Risk-Informed Deci…Workflow mining: discovering process models from event logs (2004)The ProM Framework: A New Era in Process Mining Tool Support (2005)Process mining techniques: an application to stroke care. (2008)Process Diagnostics: A Method Based on Process Mining (2009)Workflow simulation for operational decision support (2009)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)THE APPLICATION OF PETRI NETS TO WORKFLOW MANAGEMENT (1998)Context Aware Trace Clustering: Towards Improving Process Mining Results (2009)A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs (2012)Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and Simplicity (2014)Business Process Management: A Survey (2003)Workflow Patterns (2003)Adeptflex—Supporting Dynamic Changes of Workflows Without Losing Control (1998)Beyond rigidity – dynamic process lifecycle support (2009)Beyond Process Mining: From the Past to Present and Future (2010)A recommendation system for predicting risks across multiple business process instances (2014)Genetic Process Mining (2005)Business process mining: An industrial application (2006)Genetic process mining: an experimental evaluation (2007)Prediction of Remaining Service Execution Time Using Stochastic Petri Nets with Arbitrary Firing Delays (2013)Using Convolutional Neural Networks for Predictive Process Analytics (2019)Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics (2007)Wanna improve process mining results? (2013)Empirical study of topic modeling in Twitter (2010)Fundamentals of Business Process Management (2013)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)An empirical comparison of classification techniques for next event prediction using business process event logs (2019)Predicting process behaviour using deep learning (2017)Predictive Business Process Monitoring with LSTM Neural Networks (2017)A Multi-View Deep Learning Approach for Predictive Business Process Monitoring (2021)Predictive process monitoring: concepts, challenges, and future research directions (2024)Modeling Control Objectives for Business Process Compliance (2007)Discovering Block-Structured Process Models from Event Logs - A Constructive Approach (2013)Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour (2014)
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References

  • 2003Workflow mining: A survey of issues and approaches1,052 cited
  • 2008Business Process Management Workshops761 cited
  • 2010Time prediction based on process mining507 cited
  • 2009Trace Clustering in Process Mining364 cited
  • 2006Discovering expressive process models by clustering log traces321 cited
  • 2008Supporting Flexible Processes through Recommendations Based on History192 cited
  • 2007ProM 4.0: Comprehensive Support for Real Process Analysis183 cited
  • 2008Cycle Time Prediction: When Will This Case Finally Be Finished?132 cited

Cited by

  • 2018Genetic algorithms for hyperparameter optimization in predictive business process monitoring111 cited
  • 2016Predictive Business Process Monitoring with Structured and Unstructured Data108 cited
  • 2017A Deep Learning Approach for Predicting Process Behaviour at Runtime105 cited
  • 2017Intra and Inter-case Features in Predictive Process Monitoring: A Tale of Two Dimensions105 cited
  • 2018A Novel Business Process Prediction Model Using a Deep Learning Method104 cited
  • 2014Data-aware remaining time prediction of business process instances100 cited
  • 2014Queue Mining – Predicting Delays in Service Processes

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92 cited
  • 2017From event streams to process models and back: Challenges and opportunities77 cited
  • 2013Supporting Risk-Informed Decisions during Business Process Execution77 cited
  • 2017Run-time prediction of business process indicators using evolutionary decision rules69 cited
  • 2014A General Framework for Correlating Business Process Characteristics64 cited
  • 2020An extended model for remaining time prediction in manufacturing systems using process mining64 cited
  • 2017A Multi-stage Deep Learning Approach for Business Process Event Prediction63 cited
  • 2019Prediction-based Resource Allocation using LSTM and Minimum Cost and Maximum Flow Algorithm62 cited
  • 2020Explainability in Predictive Process Monitoring: When Understanding Helps Improving60 cited
  • 2019From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring59 cited