Knowledge-Aware Process Mining: Conceptual Foundations and IT Artifacts for Process Mining in Knowledge-Intensive Processes / Katharina Brennig. Paderborn, 2025
Inhalt
- List of Figures
- List of Tables
- Part A: Synopsis
- Introduction
- Research Background
- Foundations of Process Mining
- Process Mining in Knowledge-Intensive Processes
- Enhancing Process Understanding and Knowledge Work with Natural Language Processing
- Research Contributions
- Paper 1 – Maximizing the Impact of Process Mining Research
- Paper 2 – Improving Process Mining Maturity
- Paper 3 – Process Mining of KIPs
- Paper 4 – Supporting Organizational Knowledge Creation in KIPs
- Paper 5 – Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of KIPs
- Paper 6 – Text-Aware Predictive Process Monitoring of KIPs
- Paper 7 – Straight outta Logs: Can LLMs overcome Preprocessing in NEP?
- Discussion and Conclusion
- Part B: Research Papers
- Maximizing the Impact of Process Mining Research: Four Strategic Guidelines
- Improving Process Mining Maturity: From Intentions to Actions
- Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing
- Supporting Organizational Knowledge Creation in Knowledge-Intensive Processes through Process Mining
- Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes
- Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?
- Straight Outta Logs: Can Large Language Models Overcome Preprocessing in Next Event Prediction?
- Bibliography