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Enhancing Predictive Process Monitoring with Time-Related Feature Engineering · Study

WorkEnhancing Predictive Process Monitoring with Time-Related Feature Engineering

Rafael S. Oyamada2024

Work2024

Enhancing Predictive Process Monitoring with Time-Related Feature Engineering

Rafael S. Oyamada · Gabriel Marques Tavares · Sylvio Barbon · Paolo Ceravolo

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

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Business Process Modeling and Analysis Data Mining Algorithms and Applications Time Series Analysis and Forecasting

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References

2016Process Mining 2017Predictive Business Process Monitoring with LSTM Neural Networks 2019Outcome-Oriented Predictive Process Monitoring 2019Learning Accurate LSTM Models of Business Processes 2019Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring 2018Time and activity sequence prediction of business process instances 2019Data Management Challenges for Deep Learning 2017LSTM networks for data-aware remaining time prediction of business process instances

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Details

Year2024

Typeother

Published2024-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations10

Files0 public / 0

ShelfBusiness Process Modeling and Analysis

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doi10.1007/978-3-031-61057-8_5

openalex_workW4399273073

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