An Innovative Next Activity Prediction Using Process Entropy and Dynamic Attribute-Wise-Transformer in Predictive Business Process Monitoring

1. 1Calculate process entropy to quantify the complexity of event logs
2. 2Apply dynamic attribute-wise-transformer to capture evolving patterns in event data
3. 3Use the entropy-based model selection framework to choose the most suitable model for next activity prediction
4. 4Evaluate the performance of the selected model using metrics such as accuracy and interpretability

Data scientists and business analysts on a team can benefit from this approach to improve operational efficiency and decision-making, as it provides a framework for selecting the most suitable model for next activity prediction

💡 Process entropy can be used to select the most suitable model for next activity prediction, balancing accuracy and interpretability

📈 Improve next activity prediction in business process monitoring with process entropy & dynamic attribute-wise-transformer!