Search Results for author:
Found 6 papers, 0 papers with code
A Discussion on Generalization in Next-Activity Prediction
Next activity prediction aims to forecast the future behavior of running process instances.
Large Language Models can accomplish Business Process Management Tasks
In this paper, we illustrate how LLMs can accomplish text-related BPM tasks by applying a specific LLM to three exemplary tasks: mining imperative process models from textual descriptions, mining declarative process models from textual descriptions, and assessing the suitability of process tasks from textual descriptions for robotic process automation.
A Reference Data Model for Process-Related User Interaction Logs
User interaction (UI) logs are high-resolution event logs that record low-level activities performed by a user during the execution of a task in an information system.
AI-Augmented Business Process Management Systems: A Research Manifesto
AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology.
XES Tensorflow - Process Prediction using the Tensorflow Deep-Learning Framework
This demo paper focuses on the software implementation and describes the architecture and user interface.
Predicting Process Behaviour using Deep Learning
Predicting business process behaviour is an important aspect of business process management.
