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Detecting Context-Aware Deviations in Process Executions
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Detecting Context-Aware Deviations in Process Executions (2022)Detecting Context-Aware Deviations in Pro…Towards a comprehensive understanding of the context concepts in context-aware business processes (2019)Towards a comprehensive under…Mining association rules for anomaly detection in dynamic process runtime behavior and explaining the root cause to users (2019)Mining association rules for …BINet: Multi-perspective business process anomaly classification (2019)BINet: Multi-perspective busi…An anomaly detection technique for business processes based on extended dynamic bayesian networks (2019)An anomaly detection techniqu…Analyzing business process anomalies using autoencoders (2018)Analyzing business process an…Multi Instance Anomaly Detection in Business Process Executions (2017)Multi Instance Anomaly Detect…Anomaly Detection in Business Process Runtime Behavior -- Challenges and Limitations (2017)Anomaly Detection in Business…A framework for detecting deviations in complex event logs (2017)A framework for detecting dev…Balanced multi-perspective checking of process conformance (2015)Balanced multi-perspective ch…Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour (2014)Discovering Block-Structured …Replaying history on process models for conformance checking and performance analysis (2012)Replaying history on process …Process Mining Put into Context (2012)Process Mining Put into Conte…Algorithms for anomaly detection of traces in logs of process aware information systems (2012)Algorithms for anomaly detect…Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints (2023)Predicting Unseen Process Beh…Workflow mining: discovering process models from event logs (2004)Process Mining (2011)Process Mining: Discovery, Conformance and Enhancement of Business Processes (2011)Process Cubes: Slicing, Dicing, Rolling Up and Drilling Down Event Data for Process Mining (2013)Business Process Simulation Survival Guide (2014)Queue mining for delay prediction in multi-class service processes (2015)The ProM Framework: A New Era in Process Mining Tool Support (2005)Process Mining Manifesto (2012)Scalable process discovery and conformance checking (2016)Automated Discovery of Process Models from Event Logs: Review and Benchmark (2018)Split miner: automated discovery of accurate and simple business process models from event logs (2018)Conformance checking of processes based on monitoring real behavior (2007)Conformance checking based on multi-perspective declarative process models (2016)Extraction, correlation, and abstraction of event data for process mining (2019)Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction (2020)Data fusion (2009)Event Log Preprocessing for Process Mining: A Review (2021)Anomaly Detection Using Process Mining (2009)Business Process Management (2013)Design Science Methodology for Information Systems and Software Engineering (2014)A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs (2015)Detecting anomalies in business process event logs using statistical leverage (2020)Keeping our rivers clean: Information-theoretic online anomaly detection for streaming business process events (2021)Process Mining and Security: Detecting Anomalous Process Executions and Checking Process Conformance (2005)Multi-perspective Anomaly Detection in Business Process Execution Events (2016)BINet: Multivariate Business Process Anomaly Detection Using Deep Learning (2018)DeepAlign: Alignment-Based Process Anomaly Correction Using Recurrent Neural Networks (2020)LSTM-Based Anomaly Detection of Process Instances: Benchmark and Tweaks (2023)Survey and Benchmark of Anomaly Detection in Business Processes (2024)The Mathematics Anxiety Rating Scale: Psychometric data. (1972)What is total quality control the japanese way (1985)Process Mining: A Guide for Practitioners (2022)Predictive compliance monitoring in process-aware information systems: State of the art, functionalities, research directions (2023)Mining process models with non-free-choice constructs (2007)Predicting process behaviour using deep learning (2017)Predictive Business Process Monitoring with LSTM Neural Networks (2017)Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event prediction with deep learning (2021)A Systematic Review of Anomaly Detection for Business Process Event Logs (2023)Large Process Models: A Vision for Business Process Management in the Age of Generative AI (2024)Process Mining (2012)Autoencoders for improving quality of process event logs (2019)
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References

  • 2012Replaying history on process models for conformance checking and performance analysis738 cited
  • 2014Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour458 cited
  • 2015Balanced multi-perspective checking of process conformance222 cited
  • 2012Process Mining Put into Context124 cited
  • 2012Algorithms for anomaly detection of traces in logs of process aware information systems118 cited
  • 2018Analyzing business process anomalies using autoencoders112 cited
  • 2019BINet: Multi-perspective business process anomaly classification96 cited
  • 2019Mining association rules for anomaly detection in dynamic process runtime behavior and explaining the root cause to users48 cited
  • 2019An anomaly detection technique for business processes based on extended dynamic bayesian networks37 cited
  • 2017Multi Instance Anomaly Detection in Business Process Executions31 cited
  • 2017A framework for detecting deviations in complex event logs23 cited
  • 2017Anomaly Detection in Business Process Runtime Behavior -- Challenges and Limitations15 cited
  • 2019Towards a comprehensive understanding of the context concepts in context-aware business processes12 cited

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  • 2023Predicting Unseen Process Behavior Based on Context Information from Compliance Constraints

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8 cited