Trace Encoding Techniques for Multi‐Perspective Process Mining: A Comparative Study
Process mining (PM) comprises a variety of methods for discovering information about
processes from their execution logs. Some of them, such as trace clustering, trace …
processes from their execution logs. Some of them, such as trace clustering, trace …
JARVIS: Joining Adversarial Training With Vision Transformers in Next-Activity Prediction
V Pasquadibisceglie, A Appice… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we propose a novel predictive process monitoring approach, named JARVIS,
that is designed to achieve a balance between accuracy and explainability in the task of next …
that is designed to achieve a balance between accuracy and explainability in the task of next …
Predictive process monitoring: concepts, challenges, and future research directions
Abstract Predictive Process Monitoring (PPM) extends classical process mining techniques
by providing predictive models that can be applied at runtime during the execution of a …
by providing predictive models that can be applied at runtime during the execution of a …
PROPHET: explainable predictive process monitoring with heterogeneous graph neural networks
V Pasquadibisceglie, R Scaringi… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
In this paper, we introduce PROPHET, an innovative approach to predictive process
monitoring based on Heterogeneous Graph Neural Networks. PROPHET is designed to …
monitoring based on Heterogeneous Graph Neural Networks. PROPHET is designed to …
Tuning machine learning to address process mining requirements
Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …
tasks like data transformation, noise reduction, anomaly detection, classification, and …
Tailoring Machine Learning for Process Mining
Machine learning models are routinely integrated into process mining pipelines to carry out
tasks like data transformation, noise reduction, anomaly detection, classification, and …
tasks like data transformation, noise reduction, anomaly detection, classification, and …
[HTML][HTML] Control-flow anomaly detection by process mining-based feature extraction and dimensionality reduction
The business processes of organizations may deviate from normal control flow due to
disruptive anomalies, including unknown, skipped, and wrongly-ordered activities. To …
disruptive anomalies, including unknown, skipped, and wrongly-ordered activities. To …
Validation set sampling strategies for predictive process monitoring
Previous studies investigating the efficacy of long short-term memory (LSTM) recurrent
neural networks in predictive process monitoring and their ability to capture the underlying …
neural networks in predictive process monitoring and their ability to capture the underlying …
Novel approach for industrial process anomaly detection based on process mining
Anomaly detection plays a critical role in ensuring the quality and safety of industrial
processes. Process mining, as an emerging technology, has proven effective in extracting …
processes. Process mining, as an emerging technology, has proven effective in extracting …
Automated Trace Clustering Pipeline Synthesis in Process Mining
Business processes have undergone a significant transformation with the advent of the
process-oriented view in organizations. The increasing complexity of business processes …
process-oriented view in organizations. The increasing complexity of business processes …