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Evaluating Trace Encoding Methods in Process Mining · Study

WorkEvaluating Trace Encoding Methods in Process Mining

Sylvio Barbon2021

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Workgreen2021

Evaluating Trace Encoding Methods in Process Mining

Sylvio Barbon · Paolo Ceravolo · Ernesto Damiani · Gabriel Marques Tavares

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

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Business Process Modeling and Analysis Data Mining Algorithms and Applications Software System Performance and Reliability

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References

2004Workflow mining: discovering process models from event logs 2007Conformance checking of processes based on monitoring real behavior 2011BPMN: An introduction to the standard 2006Workflow control-flow patterns : a revised view 2018Conformance Checking 2009Context Aware Trace Clustering: Towards Improving Process Mining Results 2015Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes 2018Time and activity sequence prediction of business process instances

Cited by

2021Semi-Supervised Anomaly Detection in Business Process Event Data using Self-Attention based Classification 2023JARVIS: Joining Adversarial Training With Vision Transformers in Next-Activity Prediction 2021A multi-perspective approach for the analysis of complex business processes behavior 2023Graph-based feature extraction on object-centric event logs 2021Process Mining Encoding via Meta-learning for an Enhanced Anomaly Detection

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2021Process Mining Encoding via Meta-learning for an Enhanced Anomaly Detectionother · 8 shared references 2024Machine learning in business process management: A systematic literature reviewreview · 6 shared references 2023Trace encoding in process mining: A survey and benchmarkingarticle · 6 shared references 2021Graph Autoencoders for Business Process Anomaly Detectionother · 6 shared references 2020Analysis of Language Inspired Trace Representation for Anomaly Detectionother · 6 shared references 2021Natural language-based detection of semantic execution anomalies in event logsarticle · 5 shared references

Details

Year2021

Typeother

Published2021-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations33

Files0 public / 0

ShelfBusiness Process Modeling and Analysis

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doi10.1007/978-3-030-70650-0_11

openalex_workW3135069918

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