Advanced Information Systems Engineering

Process mining.- Decision Mining with Time Series Data Based on Automatic Feature Generation.- Inferring A Multi-Perspective Likelihood Graph from Black-Box Next Event Predictors.- Bootstrapping Generalization of Process Models Discovered From Event Data.- Learning Accurate Business Process SimulationModels from Event Logs via Automated Process Discovery and Deep Learning.- Multi-perspective Process Analysis: Mining the Association between Control Flow and Data Objects.- Sustainable and explainable applications.- Towards Greener Applications: Enabling Sustainable-aware Cloud Native Applications Design.- Towards Explainable Artificial Intelligence in Financial Fraud Detection: Using Shapley Additive Explanations to Explore Feature Importance.- Tools and methods to support research and design.- Systematic Literature Review Search Query Refinement Pipeline: Incremental Enrichment and Adaptation.- A model-driven approach for systematic reproducibility and replicability of data science projects.- The Aircraft and its Manufacturing System: From Early Requirements to Global Design.- Process modeling.- Causal Reasoning over Decisions in Process Models.- Crop Harvest Forecast via Agronomy-informed Process Modelling and Predictive Monitoring.- Guiding Knowledge Workers under Dynamic Contexts.- Natural language processing techniques in IS engineering.- Context Knowledge-aware Recognition of Composite Intents in Task-oriented Human-Bot Conversations.- Crowdsourcing syntactically diverse paraphrases with diversity-aware prompts and workflows.- A Subject-aware Attention Hierarchical Tagger for Joint Entity and Relation Extraction.- Process monitoring and simulation.- Estimating Activity Start Timestamps in the presence of Waiting Times via Process Simulation.- Updating prediction models for predictive process monitoring.- Multi-Model Monitoring Framework for Hybrid Process Specifications.-