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Updating Prediction Models for Predictive Process Monitoring · Study

WorkUpdating Prediction Models for Predictive Process Monitoring

Alfonso Eduardo Marquez-Chamorro2022

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Workgreen2022

Updating Prediction Models for Predictive Process Monitoring

Alfonso Eduardo Marquez-Chamorro · Isabel A. Nepomuceno-Chamorro · Manuel Resinas · Antonio Ruiz–Cortés

14 citations·0/0 files stored·Lecture notes in computer science

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Business Process Modeling and Analysis Forecasting Techniques and Applications Robotic Process Automation Applications

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References

2017Predictive Monitoring of Business Processes: A Survey 2015A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs 2019Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring 2011Handling Concept Drift in Process Mining 2013Dealing With Concept Drifts in Process Mining 2018Time and activity sequence prediction of business process instances 2012Discovering Context-Aware Models for Predicting Business Process Performances 2017Detecting sudden and gradual drifts in business processes from execution traces

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Details

Year2022

Typeother

Published2022-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations14

Files0 public / 0

ShelfBusiness Process Modeling and Analysis

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doi10.1007/978-3-031-07472-1_18

openalex_workW4285294863

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