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Analyzing Process Concept Drifts Based on Sensor Event Streams During Runtime
12 references·4 citing·34 second hop
Analyzing Process Concept Drifts Based on Sensor Event Streams During Runtime (2020)Analyzing Process Concept Drifts Based on…Comprehensive process drift analysis with the visual drift detection tool (2019)Comprehensive process drift a…Event-based failure prediction in distributed business processes (2017)Event-based failure predictio…Event stream-based process discovery using abstract representations (2017)Event stream-based process di…Detecting sudden and gradual drifts in business processes from execution traces (2017)Detecting sudden and gradual …Detecting Sudden and Gradual Drifts in Business Processes from Execution Traces (2017)Detecting Sudden and Gradual …Process Mining (2016)Process MiningFundamentals of Business Intelligence (2015)Fundamentals of Business Inte…Control-flow discovery from event streams (2014)Control-flow discovery from e…Online Process Discovery to Detect Concept Drifts in LTL-Based Declarative Process Models (2013)Online Process Discovery to D…Discovering Block-Structured Process Models from Event Logs - A Constructive Approach (2013)Discovering Block-Structured …Dealing With Concept Drifts in Process Mining (2013)Dealing With Concept Drifts i…Heuristics Miners for Streaming Event Data (2012)Heuristics Miners for Streami…Process Mining—Discovery, Conformance, and Enhancement of Manufacturing Processes (2023)Process Mining—Discovery, Con…Decision Mining with Time Series Data Based on Automatic Feature Generation (2022)Decision Mining with Time Ser…Process Automation and Process Mining in Manufacturing (2021)Process Automation and Proces…Assessing the Impact of Context Data on Process Outcomes During Runtime (2021)Assessing the Impact of Conte…CONTINUOUS INSPECTION SCHEMES (1954)YAWL: yet another workflow language (2004)Process Mining (2011)Adoption, use and management of process mining in practice (2020)A Survey on Concept Drift in Process Mining (2021)Big data: The next frontier for innovation, competition, and productivity (2011)Process Mining: Discovery, Conformance and Enhancement of Business Processes (2011)Detecting Drift from Event Streams of Unpredictable Business Processes (2016)A Framework for Online Conformance Checking (2018)Online Conformance Checking Using Behavioural Patterns (2018)Workflow mining: discovering process models from event logs (2004)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)THE APPLICATION OF PETRI NETS TO WORKFLOW MANAGEMENT (1998)Fire now, fire later: alarm-based systems for prescriptive process monitoring (2021)A Systematic Review of Anomaly Detection for Business Process Event Logs (2023)Artificial Intelligence and Knowledge Management: Impacts, Benefits, and Implementation (2023)Fundamentals of Business Process Management (2013)Scientific method: Statistical errors (2014)Evaluation Goals for Online Process Mining: A Concept Drift Perspective (2020)Recommendations for enhancing the usability and understandability of process mining in healthcare (2020)Visual Drift Detection for Event Sequence Data of Business Processes (2021)Optimal Detection of Changepoints With a Linear Computational Cost (2012)A Framework for Explainable Concept Drift Detection in Process Mining (2021)Explainable concept drift in process mining (2023)Discovering instance and process spanning constraints from process execution logs (2019)Amplifying organizational performance from business intelligence: Business analytics implementation in the retail industry (2022)Predictive compliance monitoring in process-aware information systems: State of the art, functionalities, research directions (2023)Using Process Mining to Support Theorizing About Change in Organizations (2020)Online Discovery of Declarative Process Models from Event Streams (2015)Scalable Process Discovery with Guarantees (2015)Outcome-Oriented Predictive Process Monitoring (2019)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
  • 2013Discovering Block-Structured Process Models from Event Logs - A Constructive Approach648 cited
  • 2013Dealing With Concept Drifts in Process Mining192 cited
  • 2017Detecting sudden and gradual drifts in business processes from execution traces94 cited
  • 2017Detecting Sudden and Gradual Drifts in Business Processes from Execution Traces86 cited
  • 2014Control-flow discovery from event streams86 cited
  • 2017Event stream-based process discovery using abstract representations81 cited
  • 2012Heuristics Miners for Streaming Event Data64 cited
  • 2015Fundamentals of Business Intelligence55 cited
  • 2019Comprehensive process drift analysis with the visual drift detection tool51 cited
  • 2013Online Process Discovery to Detect Concept Drifts in LTL-Based Declarative Process Models50 cited
  • 2017Event-based failure prediction in distributed business processes45 cited

Cited by

  • 2021Process Automation and Process Mining in Manufacturing25 cited
  • 2022Decision Mining with Time Series Data Based on Automatic Feature Generation18 cited
  • 2021Assessing the Impact of Context Data on Process Outcomes During Runtime

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17 cited
  • 2023Process Mining—Discovery, Conformance, and Enhancement of Manufacturing Processes17 cited