Search Results for author:
Found 4 papers, 4 papers with code
Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction
Predictive process monitoring aims to predict future characteristics of an ongoing process case, such as case outcome or remaining timestamp.
Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs
This paper proposes an approach to analyze an event log of a business process in order to generate case-level recommendations of treatments that maximize the probability of a given outcome.
Prescriptive Process Monitoring for Cost-Aware Cycle Time Reduction
The paper proposes a prescriptive process monitoring method that uses orthogonal random forest models to estimate the causal effect of triggering a time-reducing intervention for each ongoing case of a process.
Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning
Increasing the success rate of a process, i. e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
