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This book constitutes the refereed proceedings of the 22nd International Conference on Business Process Management, BPM 2024, which took place in Krakow, Poland, in September 2024. The 29 full papers included in this book were carefully reviewed and selected from 144 submissions. They were organized in topical sections as follows: Foundations; Engineering; and Management. .
This book constitutes the refereed proceedings of the 22nd International Conference on Business Process Management, BPM 2024, which took place in Krakow, Poland, in September 2024.
The 29 full papers included in this book were carefully reviewed and selected from 144 submissions. They were organized in topical sections as follows: Foundations; Engineering; and Management.
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Inhaltsangabe
Foundations.- Optimizing Resource-Driven Process Configuration through Genetic Algorithms.- Data Petri Nets meet Probabilistic Programming.- Conformance Checking of Fuzzy Logs against Declarative Temporal Specifications.- Object Synchronizations and Specializations with Silent Objects in Object-Centric Petri Nets.- Glocal Conformance Checking.- On the interplay between BPMN collaborations and the physical environment.- Super Variants.- Repairing Process Models through Simulation and Explainable AI.- Improving Process Discovery Using Translucent Activity Relationships.- Engineering.- Optimizing Resource Allocation Policies in Real-World Business Processes using Hybrid Process Simulation and Deep Reinforcement Learning.- Exploiting general purpose big-data frameworks in process mining: the case of declarative process discovery.- Attention Please: What Transformer Models Really Learn for Process Prediction.- GEDI: Generating Event Data with Intentional Features for Benchmarking Process Mining.- Efficient Training of Recurrent Neural Networks for Remaining Time Prediction in Predictive Process Monitoring.- What's Behind the Screen? Unveiling UI Hierarchies in Process-Related UI Logs.- Looking for Change: A Computer Vision Approach for Concept Drift Detection in Process Mining.- Mining Behavioral Patterns for Conformance Diagnostics.- xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence Models.- CoSMo: a Framework to Instantiate Conditioned Process Simulation Models.- Experience Based Resource Allocation for Remaining Time Optimization.- Uncovering patterns for local explanations in outcome-based Predictive Process Monitoring.- Beyond Log and Model Moves in Conformance Checking: Discovering Process-Level Deviation Patterns.- Management.- Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring.- Categories of Business Value of Robotic Process Automation: A Study of Benefits and Challenges.- Anticipating Data Inaccuracy Consequences in Business Processes: An Empirical Study.- SCP-BP Framework: Situational Crime Prevention for Managing Data Breaches in Business Processes.- LLM-Assisted Optimization of Waiting Time in Business Processes: A Prompting Method.- Exploring the Cognitive Effects of Ambiguity in Process Models.- Techno-empowerment of Process Automation: Understanding Employee Acceptance of Autonomous AI in Business Processes.
Foundations.- Optimizing Resource-Driven Process Configuration through Genetic Algorithms.- Data Petri Nets meet Probabilistic Programming.- Conformance Checking of Fuzzy Logs against Declarative Temporal Specifications.- Object Synchronizations and Specializations with Silent Objects in Object-Centric Petri Nets.- Glocal Conformance Checking.- On the interplay between BPMN collaborations and the physical environment.- Super Variants.- Repairing Process Models through Simulation and Explainable AI.- Improving Process Discovery Using Translucent Activity Relationships.- Engineering.- Optimizing Resource Allocation Policies in Real-World Business Processes using Hybrid Process Simulation and Deep Reinforcement Learning.- Exploiting general purpose big-data frameworks in process mining: the case of declarative process discovery.- Attention Please: What Transformer Models Really Learn for Process Prediction.- GEDI: Generating Event Data with Intentional Features for Benchmarking Process Mining.- Efficient Training of Recurrent Neural Networks for Remaining Time Prediction in Predictive Process Monitoring.- What's Behind the Screen? Unveiling UI Hierarchies in Process-Related UI Logs.- Looking for Change: A Computer Vision Approach for Concept Drift Detection in Process Mining.- Mining Behavioral Patterns for Conformance Diagnostics.- xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence Models.- CoSMo: a Framework to Instantiate Conditioned Process Simulation Models.- Experience Based Resource Allocation for Remaining Time Optimization.- Uncovering patterns for local explanations in outcome-based Predictive Process Monitoring.- Beyond Log and Model Moves in Conformance Checking: Discovering Process-Level Deviation Patterns.- Management.- Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring.- Categories of Business Value of Robotic Process Automation: A Study of Benefits and Challenges.- Anticipating Data Inaccuracy Consequences in Business Processes: An Empirical Study.- SCP-BP Framework: Situational Crime Prevention for Managing Data Breaches in Business Processes.- LLM-Assisted Optimization of Waiting Time in Business Processes: A Prompting Method.- Exploring the Cognitive Effects of Ambiguity in Process Models.- Techno-empowerment of Process Automation: Understanding Employee Acceptance of Autonomous AI in Business Processes.
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