Business Process Management

Research Track I: Foundations.- Efficient Optimal Alignment between Dynamic Condition Response Graphs and Traces.- Can I Trust My Simulation Model? Measuring the Quality of Business Process Simulation Models.- Event Abstraction for Partial Order Patterns.- Incremental Discovery of Process Models Using Trace Fragments.- Approximating Multi-Perspective Trace Alignment Using Trace Encoding.- POWL: Partially Ordered Workflow Language.- Polynomial-Time Conformance Checking for Process Trees.- Research Track II: Engineering.- Investigating the Influence of Data-aware Process States on Activity Probabilities in Simulation Models: Does Accuracy Improve.- yLoPro: Profiling the Dynamics of Event Logs.- Does This Make Sense? Machine Learning-based Detection of Semantic Anomalies in Business Processes.- Inferring Missing Entity Identifiers from Context using Event Knowledge Graphs.- Process Channels: A New Layer for Process Enactment Based on Blockchain State Channels.- Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems.- Context-Based Activity Label-Splitting.- Verifying Resource Compliance Requirements From Natural Language Text Over Event Logs.- From Text to Performance Measurement: Automatically Computing Process Performance using Textual Descriptions and Event Logs.- Agent Miner: An Algorithm for Discovering Agent Systems from Event Data.- Interactive Multi-Interest Process Pattern Discovery.- Research Track III: Management.- Increasing RPA adoption: An experiment on countermeasures for status quo bias.- Stochastic-Aware Comparative Process Mining in Healthcare.- On the Cognitive Effects of Abstraction and Fragmentation in Modularized Process Models.-Not Here, But There: Human Resource Allocation Patterns.- A Novel Multi-Perspective Trace Clustering Technique for IoT-enhanced Processes: A Case Study in Smart Manufacturing.- The Impact of Process Complexity on Process Performance: A Study using Event Log Data.- Deviation from