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Code for fine-tuning BERT for labeling textual values in events with process-related semantic roles
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Trained models for extracting semantic process information from event data.
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The repository contains the implementation employed in the paper "Natural Language-based Detection of Semantic Execution Anomalies in Event Logs" by Han van der Aa, Adrian Rebmann, and Henrik Leopold, published in Information Systems (2021)
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Multi-Order Concept Drift Detection in Business Processes
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Supplementary material for a conference submission
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This includes supplementary files of the DDPS methodology by Oberle & van der Aa (2023)
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This project provides a prototype of the approach that assesses runtime process flexibility using vector autoregressive modeling
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