Lecture Notes in Business Information Processing

Rethinking the Input for Process Mining: Insights from the XES Survey and Workshop.- Probability Estimation of Uncertain Process Trace Realizations.- Visualizing Trace Variants From Partially Ordered Event Data.- Analyzing Multi-level BOM-structured Event Data.- Linac: A Smart Environment Simulator of Human Activities.- Root Cause Analysis in Process Mining with Probabilistic Temporal Logic.- xPM: A Framework for Process Mining with Exogenous Data.- A Bridging Model for Process Mining and IoT.- Exploiting Instance Graphs and Graph Neural Networks for next activity prediction.- Can deep neural networks learn process modelstructure? An assessment framework and analysis.- Remaining Time Prediction for Processes with Inter-Case Dynamics.- Event Log Sampling for Predictive Monitoring.- Active Anomaly Detection for Key Item Selection in Process Auditing.- Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach.- Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring.- Online Prediction of Aggregated Retailer Consumer Behaviour.- PErrCas: Process Error Cascade Mining in Trace Streams.- Continuous performance evaluation for business process outcome monitoring.- An Event Data Extraction Approach from SAP ERP for Process Mining.- Towards a Natural Language Conversational Interface for Process Mining.- On the Performance Analysis of the Adversarial System Variant Approximation Method to Quantify Process Model Generalization.- Verifying guideline compliance in clinical treatment using multi-perspective conformance checking: a case study.- Patient Discharge Classification based on the Hospital Treatment Process.- Combining the Clinical and Operational Perspectives in Heterogeneous Treatment E ect Inference in Healthcare Processes.- Interactive Process Mining Applied in a Cardiology Outpatient Department.- Discovering care pathways for multi-morbid patients using event graphs.- Process Mining in Trusted Execution Environments: Towards Hardware Guarantees for Trust-aware Inter-organizational Process Analysis.- Quantifying the Re-identification Risk in Published Process Models.- Trustworthy Artificial Intelligence and Process Mining: Challenges and Opportunities.