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22nd Business Process Management 2024: Krakow, Poland
- Andrea Marrella
, Manuel Resinas
Business Process Management - 22nd International Conference, BPM 2024, Krakow, Poland, September 1-6, 2024, Proceedings. Lecture Notes in Computer Science 14940, Springer 2024, ISBN 978-3-031-70395-9
Foundations
- Felix Schumann
Optimizing Resource-Driven Process Configuration Through Genetic Algorithms. 3-20 - Martin Kuhn, Joscha Grüger, Christoph Matheja, Andrey Rivkin:
Data Petri Nets Meet Probabilistic Programming. 21-38 - Ivan Donadello
Conformance Checking of Fuzzy Logs Against Declarative Temporal Specifications. 39-56 - Jan Niklas van Detten, Pol Schumacher, Sander J. J. Leemans:
Object Synchronizations and Specializations with Silent Objects in Object-Centric Petri Nets. 57-74 - Alessandro Burigana, Alessandro Gianola, Marco Montali, Sarah Winkler:
Glocal Conformance Checking. 75-92 - Flavio Corradini
On the Interplay Between BPMN Collaborations and the Physical Environment. 93-110 - Jan Niklas Adams
Super Variants. 111-128 - Francesco Vinci, Massimiliano de Leoni:
Repairing Process Models Through Simulation and Explainable AI. 129-145 - Harry H. Beyel
Improving Process Discovery Using Translucent Activity Relationships. 146-163
Engineering
- Francesca Meneghello, Jeroen Middelhuis, Laura Genga, Zaharah Bukhsh, Massimiliano Ronzani, Chiara Di Francescomarino, Chiara Ghidini, Remco M. Dijkman:
Optimizing Resource Allocation Policies in Real-World Business Processes Using Hybrid Process Simulation and Deep Reinforcement Learning. 167-184 - Ioannis Mavroudopoulos, Konstantinos Varvoutas, Georgia Kougka, Anastasios Gounaris, Marco Comuzzi:
Exploiting General Purpose Big-Data Frameworks in Process Mining: The Case of Declarative Process Discovery. 185-202 - Martin Käppel
Attention Please: What Transformer Models Really Learn for Process Prediction. 203-220 - Andrea Maldonado, Christian M. M. Frey, Gabriel Marques Tavares, Nikolina Rehwald, Thomas Seidl:
GEDI: Generating Event Data with Intentional Features for Benchmarking Process Mining. 221-237 - Johannes Roider, Dario Zanca, Bjoern M. Eskofier:
Efficient Training of Recurrent Neural Networks for Remaining Time Prediction in Predictive Process Monitoring. 238-255 - Antonio Martínez-Rojas
What's Behind the Screen? Unveiling UI Hierarchies in Process-Related UI Logs. 256-272 - Alexander Kraus, Han van der Aa:
Looking for Change: A Computer Vision Approach for Concept Drift Detection in Process Mining. 273-290 - Eduardo Goulart Rocha
Mining Behavioral Patterns for Conformance Diagnostics. 291-308 - Kiran Busch, Timotheus Kampik, Henrik Leopold:
xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence Models. 309-327 - Rafael Seidi Oyamada
CoSMo: A Framework to Instantiate Conditioned Process Simulation Models. 328-344 - Alessandro Padella, Felix Mannhardt, Francesco Vinci, Massimiliano de Leoni, Irene Vanderfeesten
Experience-Based Resource Allocation for Remaining Time Optimization. 345-362 - Andrei Buliga, Mozhgan Vazifehdoostirani
Uncovering Patterns for Local Explanations in Outcome-Based Predictive Process Monitoring. 363-380 - Michael Grohs
Beyond Log and Model Moves in Conformance Checking: Discovering Process-Level Deviation Patterns. 381-399
Management
- Kateryna Kubrak, Lana Botchorishvili, Fredrik Milani, Alexander Nolte, Marlon Dumas:
Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring. 403-420 - Maximilian Vitzethum, Alexander Mayr, Christian Janiesch
Categories of Business Value of Robotic Process Automation: A Study of Benefits and Challenges. 421-438 - Yotam Evron, Pnina Soffer, Anna Zamansky:
Anticipating Data Inaccuracy Consequences in Business Processes: an Empirical Study. 439-455 - Cheng Miao
Scp-bp Framework: Situational Crime Prevention for Managing Data Breaches in Business Processes. 456-473 - Katsiaryna Lashkevich
LLM-Assisted Optimization of Waiting Time in Business Processes: A Prompting Method. 474-492 - Marco Franceschetti, Amine Abbad Andaloussi, Clemens Schreiber, Hugo A. López
Exploring the Cognitive Effects of Ambiguity in Process Models. 493-510 - Artur Modlinski
Techno-empowerment of Process Automation: Understanding Employee Acceptance of Autonomous AI in Business Processes. 511-527
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