Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration
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Abstract (arXiv)
Business processes that involve AI-powered automation have been gaining importance and market share in recent years. These business processes combine the characteristics of classical business process management, goal-driven chatbots, conversational recommendation systems, and robotic process automation. In the new context, prescriptive process monitoring demands innovative approaches. Unfortunately, data logs from these new processes are still not available in the public domain. We describe the main challenges in this new domain and introduce a synthesized dataset that is based on an actual use case of intelligent process automation with chatbot orchestration. Using this dataset, we demonstrate crowd-wisdom and goal-driven approaches to prescriptive process monitoring.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 16 of its 28 references that are in the map. First posted on arXiv 13 Dec 2022.
Builds on
16 of 28 references.
References · 16
- 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 766
- 2021Reinforcement learning based recommender systems: A surveycited by 188
- 2019Not Enough Data? Deep Learning to the Rescue!cited by 175
- 2015The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systemscited by 172
- 2017ParlAI: A Dialog Research Software Platformcited by 139
- 2020DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialoguecited by 89
- 2020Schema-Guided Dialogue State Tracking Task at DSTC8cited by 32
- 2021A systematic literature review on state-of-the-art deep learning methods for process predictioncited by 32
- 2017BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systemscited by 30
- 2022AI-Augmented Business Process Management Systems: A Research Manifestocited by 28
- 2018Predictive Process Monitoring Methods: Which One Suits Me Best?cited by 27
- 2020Explainable Predictive Process Monitoringcited by 27
4 more
- 2018Alarm-Based Prescriptive Process Monitoringcited by 16
- 2020Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logscited by 15
- 2021Prescriptive Process Monitoring: Quo Vadis?cited by 15
- 2020A Conversational Digital Assistant for Intelligent Process Automationcited by 8
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Citing papers per year: 2024: 2; 2025: 1; 2026: 3.
6 papers.
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- 2025From Benchmarks to Business Impact: Deploying IBM Generalist Agent in Enterprise Productioncited by 5
- 2026Governance by Construction for Generalist Agentscited by 1
- 2026BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AIcited by 0
- 2026BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AI27 Aug 2026
- 2026Governance by Construction for Generalist Agents20 May 2026
- 2026AgentFixer: From Failure Detection to Fix Recommendations in LLM Agentic Systems18 Feb 2026
- 2025From Benchmarks to Business Impact: Deploying IBM Generalist Agent in Enterprise Production27 Oct 2025
- 2024ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents9 Oct 2024
- 2024SNAP: Semantic Stories for Next Activity Prediction28 Jan 2024