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ORCIDWil M. P. van der Aalst
Willibrordus Martinus Pancratius van der Aalst
Person information
- affiliation: RWTH Aachen University, Chair of Process and Data Science, Germany
- affiliation (former): Eindhoven University of Technology, Department of Mathematics and Computer Science
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2020 – today
- 2024
[j293]Paolo Ceravolo
, Sylvio Barbon Junior, Ernesto Damiani, Wil M. P. van der Aalst:
Tuning Machine Learning to Address Process Mining Requirements. IEEE Access 12: 24583-24595 (2024)- [j292]Christof Weinhardt, Jonas Fegert, Oliver Hinz, Wil M. P. van der Aalst:
Digital Democracy: A Wake-Up Call. Bus. Inf. Syst. Eng. 66(2): 127-134 (2024) - [j291]Wil M. P. van der Aalst:
Matthias Jarke (1952-2024), A Pioneer in Information Systems and Data Management. Bus. Inf. Syst. Eng. 66(2): 135 (2024) - [j290]Björn Hanneke, Oliver Hinz, Jella Pfeiffer, Wil M. P. van der Aalst:
The Internet of Value: Unleashing the Blockchain's Potential with Tokenization. Bus. Inf. Syst. Eng. 66(4): 411-419 (2024) - [j289]Moe Thandar Wynn, Wil M. P. van der Aalst, Eric Verbeek, Bruno N. Di Stefano:
The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs]. IEEE Comput. Intell. Mag. 19(1): 20-23 (2024) - [j288]Lisa Luise Mannel, Wil M. P. van der Aalst:
Discovering Process Models with Long-Term Dependencies while Providing Guarantees and Filtering Infrequent Behavior Patterns. Fundam. Informaticae 190(2-4): 109-158 (2024) - [j287]Alessandro Berti, Johannes Herforth, Mahnaz Sadat Qafari, Wil M. P. van der Aalst:
Graph-based feature extraction on object-centric event logs. Int. J. Data Sci. Anal. 18(2): 139-155 (2024) - [j286]Adam T. Burke, Sander J. J. Leemans, Moe Thandar Wynn, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede:
A chance for models to show their quality: Stochastic process model-log dimensions. Inf. Syst. 124: 102382 (2024) - [j285]Daniel Schuster, Francesca Zerbato, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Defining and visualizing process execution variants from partially ordered event data. Inf. Sci. 657: 119958 (2024) - [j284]Daniel Schuster, Elisabetta Benevento, Davide Aloini, Wil M. P. van der Aalst:
Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World Application. J. Heal. Informatics Res. 8(3): 523-554 (2024) - [j283]Harry H. Beyel, Omar Makke, Mahsa Pourbafrani, Oleg Gusikhin, Wil M. P. van der Aalst:
Analyzing Data Streams from Cyber-Physical-Systems: A Case Study. SN Comput. Sci. 5(6): 706 (2024) - [j282]Edyta Brzychczy, Agnieszka Zuber, Wil M. P. van der Aalst:
Process Mining of Mining Processes: Analyzing Longwall Coal Excavation Using Event Data. IEEE Trans. Syst. Man Cybern. Syst. 54(5): 2723-2734 (2024) - [c648]Wil M. P. van der Aalst:
Lifting Process Discovery and Conformance Checking to the Next Level: A General Approach to Object-Centric Process Mining (Invited Talk). PNSE@Petri Nets 2024: 1-12 - [c647]Tobias Brockhoff, Moritz Nicolas Gose, Merih Seran Uysal, Wil M. P. van der Aalst:
Process Comparison Using Petri Net Decomposition. Petri Nets 2024: 83-105 - [c646]Harry H. Beyel, Marlo Verket, Viki Peeva, Christian Rennert, Marco Pegoraro, Katharina Schütt, Wil M. P. van der Aalst, Nikolaus Marx:
Process-Aware Analysis of Treatment Paths in Heart Failure Patients: A Case Study. BIOSTEC (2) 2024: 506-515 - [c645]Aaron Küsters, Wil M. P. van der Aalst:
Rust4PM: A Versatile Process Mining Library for When Performance Matters. BPM (Demos / Resources Forum) 2024: 91-95 - [c644]Lukas Liss, Jan Niklas Adams, Wil M. P. van der Aalst:
TOTeM: Temporal Object Type Model for Object-Centric Process Mining. BPM (Forum) 2024: 107-123 - [c643]Jan Niklas Adams, Emilie Hastrup-Kiil, Gyunam Park, Wil M. P. van der Aalst:
Super Variants. BPM 2024: 111-128 - [c642]Alessandro Berti, Wil M. P. van der Aalst:
CSV-PM-LLM-Parsing: Automatic Ingestion of CSV Event Logs for Process Mining using LLMs. BPM (Demos / Resources Forum) 2024: 131-135 - [c641]Harry H. Beyel, Wil M. P. van der Aalst:
Improving Process Discovery Using Translucent Activity Relationships. BPM 2024: 146-163 - [c640]Alessandro Berti, Urszula Jessen, Wil M. P. van der Aalst, Dirk Fahland:
Explainable Object-Centric Anomaly Detection: the Role of Domain Knowledge. BPM (Demos / Resources Forum) 2024: 162-168 - [c639]Gyunam Park, Jan Niklas Adams, Wil M. P. van der Aalst:
Conformance Checking and Performance Analysis Using Object-Centric Directly-Follows Graphs. BPM (Forum) 2024: 179-196 - [c638]Eduardo Goulart Rocha, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Mining Behavioral Patterns for Conformance Diagnostics. BPM 2024: 291-308 - [c637]Eduardo Goulart Rocha, Wil M. P. van der Aalst:
Precision-Guided Minimization of Arbitrary Declarative Process Models. BPMDS/EMMSAD@CAiSE 2024: 48-56 - [c636]Ali Norouzifar, Majid Rafiei, Marcus Dees, Wil M. P. van der Aalst:
Process Variant Analysis Across Continuous Features: A Novel Framework. BPMDS/EMMSAD@CAiSE 2024: 129-142 - [c635]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Process Modeling with Large Language Models. BPMDS/EMMSAD@CAiSE 2024: 229-244 - [c634]Tsung-Hao Huang, Enzo Schneider, Marco Pegoraro, Wil M. P. van der Aalst:
Fast & Sound: Accelerating Synthesis-Rules-Based Process Discovery. BPMDS/EMMSAD@CAiSE 2024: 259-274 - [c633]István Koren, Matthias Jarke, Judith Michael, Malte Heithoff, Leah Tacke genannt Unterberg, Max Stachon, Bernhard Rumpe, Wil M. P. van der Aalst:
Navigating the Data Model Divide in Smart Manufacturing: An Empirical Investigation for Enhanced AI Integration. BPMDS/EMMSAD@CAiSE 2024: 275-290 - [c632]Tobias Brockhoff, Merih Seran Uysal, Wil M. P. van der Aalst:
Process Comparison Based on Selection-Projection Structures. CAiSE 2024: 20-35 - [c631]Gyunam Park, Majid Rafiei, Hayyan Helal, Gerhard Lakemeyer, Wil M. P. van der Aalst:
Incorporating Behavioral Recommendations Mined from Event Logs into AI Planning. CAiSE Forum 2024: 20-28 - [c630]Tsung-Hao Huang, Tarek Junied, Marco Pegoraro, Wil M. P. van der Aalst:
ProReco: A Process Discovery Recommender System. CAiSE Forum 2024: 93-101 - [c629]Dina Kretzschmann, Gyunam Park, Alessandro Berti, Wil M. P. van der Aalst:
Overstock Problems in a Purchase-to-Pay Process: An Object-Centric Process Mining Case Study. CAiSE Workshops 2024: 347-359 - [c628]Harry H. Beyel, Sovin Manuel, Wil M. P. van der Aalst:
ActivityGen: Extracting Enabled Activities from Screenshots. ECAI 2024: 712-720 - [c627]Jan Niklas Adams, Hannes Drescher, Andreas Swoboda, Nikou Günnemann, Gyunam Park, Wil M. P. van der Aalst:
Improving Predictive Process Monitoring Using Object-Centric Process Mining. ECIS 2024 - [c626]Hauke Heidemeyer, Leo Auhagen, Raphael W. Majeed, Marco Pegoraro, Jonas Bienzeisler, Viki Peeva, Harry H. Beyel, Rainer Röhrig, Wil M. P. van der Aalst, Behrus Puladi:
A Pipeline for the Usage of the Core Data Set of the Medical Informatics Initiative for Process Mining - A Technical Case Report. GMDS 2024: 30-39 - [c625]Tobias Brockhoff, Merih Seran Uysal, Wil M. P. van der Aalst:
Wasserstein Weight Estimation for Stochastic Petri Nets. ICPM 2024: 81-88 - [c624]Henrik Kämmerling, Eduardo Goulart Rocha, Wil M. P. van der Aalst:
ProM4Py - A Python Wrapper For The ProM Framework. ICPM Doctoral Consortium / Demo 2024 - [c623]Eduardo Goulart Rocha, Sander J. J. Leemans, Wil M. P. van der Aalst:
Stochastic Conformance Checking Based on Expected Subtrace Frequency. ICPM 2024: 73-80 - [c622]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
ProMoAI: Process Modeling with Generative AI. IJCAI 2024: 8708-8712 - [c621]Leah Tacke genannt Unterberg, István Koren, Wil M. P. van der Aalst:
Maximizing Reuse and Interoperability in Industry 4.0 with a Minimal Data Exchange Format for Machine Data. Modellierung 2024: 103-118 - [c620]Harry Herbert Beyel, Wil M. P. van der Aalst:
Translucent Precision: Exploiting Enabling Information to Evaluate the Quality of Process Models. RCIS (2) 2024: 29-37 - [c619]Ali Norouzifar, Marcus Dees, Wil M. P. van der Aalst:
Imposing Rules in Process Discovery: An Inductive Mining Approach. RCIS (1) 2024: 220-236 - [d3]Nico Elbert, Lukas Liss, Wil M. P. van der Aalst, Christoph M. Flath:
Game Data Event Log from Age of Empire Interactions. Zenodo, 2024
- [i142]Aaron Küsters, Wil M. P. van der Aalst:
Developing a High-Performance Process Mining Library with Java and Python Bindings in Rust. CoRR abs/2401.14149 (2024) - [i141]Alessandro Berti, István Koren, Jan Niklas Adams, Gyunam Park, Benedikt Knopp, Nina Graves, Majid Rafiei, Lukas Liß, Leah Tacke genannt Unterberg, Yisong Zhang, Christopher T. Schwanen, Marco Pegoraro, Wil M. P. van der Aalst:
OCEL (Object-Centric Event Log) 2.0 Specification. CoRR abs/2403.01975 (2024) - [i140]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
ProMoAI: Process Modeling with Generative AI. CoRR abs/2403.04327 (2024) - [i139]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Process Modeling With Large Language Models. CoRR abs/2403.07541 (2024) - [i138]Harry H. Beyel, Marlo Verket, Viki Peeva, Christian Rennert, Marco Pegoraro, Katharina Schütt, Wil M. P. van der Aalst, Nikolaus Marx:
Process-Aware Analysis of Treatment Paths in Heart Failure Patients: A Case Study. CoRR abs/2403.10544 (2024) - [i137]Bianka Bakullari, Wil M. P. van der Aalst:
High-Level Event Mining: Overview and Future Work. CoRR abs/2405.14435 (2024) - [i136]Ali Norouzifar, Majid Rafiei, Marcus Dees, Wil M. P. van der Aalst:
Process Variant Analysis Across Continuous Features: A Novel Framework. CoRR abs/2406.04347 (2024) - [i135]Alessandro Berti, Urszula Jessen, Wil M. P. van der Aalst, Dirk Fahland:
Challenges of Anomaly Detection in the Object-Centric Setting: Dimensions and the Role of Domain Knowledge. CoRR abs/2407.09023 (2024) - [i134]Alessandro Berti, Humam Kourani, Wil M. P. van der Aalst:
PM-LLM-Benchmark: Evaluating Large Language Models on Process Mining Tasks. CoRR abs/2407.13244 (2024) - [i133]Humam Kourani, Alessandro Berti, Jasmin Henrich, Wolfgang Kratsch, Robin Weidlich, Chiao-Yun Li, Ahmad Arslan, Daniel Schuster, Wil M. P. van der Aalst:
Leveraging Large Language Models for Enhanced Process Model Comprehension. CoRR abs/2408.08892 (2024) - [i132]Ali Norouzifar, Humam Kourani, Marcus Dees, Wil M. P. van der Aalst:
Bridging Domain Knowledge and Process Discovery Using Large Language Models. CoRR abs/2408.17316 (2024) - [i131]Ali Norouzifar, Marcus Dees, Wil M. P. van der Aalst:
Imposing Rules in Process Discovery: an Inductive Mining Approach. CoRR abs/2408.17326 (2024) - [i130]Christian Rennert, Mahsa Pourbafrani, Wil M. P. van der Aalst:
Evaluation of Study Plans using Partial Orders. CoRR abs/2410.03314 (2024) - [i129]Dirk Fahland, Marco Montali, Julian Lebherz, Wil M. P. van der Aalst, Maarten van Asseldonk, Peter Blank, Lien Bosmans, Marcus Brenscheidt, Claudio Di Ciccio, Andrea Delgado, Daniel Calegari, Jari Peeperkorn, Eric Verbeek, Lotte Vugs, Moe Thandar Wynn:
Towards a Simple and Extensible Standard for Object-Centric Event Data (OCED) - Core Model, Design Space, and Lessons Learned. CoRR abs/2410.14495 (2024) - 2023
- [j281]Majid Rafiei, Wil M. P. van der Aalst:
An Abstraction-Based Approach for Privacy-Aware Federated Process Mining. IEEE Access 11: 33697-33714 (2023) - [j280]Wil M. P. van der Aalst, Oliver Hinz, Christof Weinhardt:
Sustainable Systems Engineering. Bus. Inf. Syst. Eng. 65(1): 1-6 (2023) - [j279]Timm Teubner, Christoph M. Flath, Christof Weinhardt, Wil M. P. van der Aalst, Oliver Hinz:
Welcome to the Era of ChatGPT et al. Bus. Inf. Syst. Eng. 65(2): 95-101 (2023) - [j278]Michael Nofer, Kevin Bauer, Oliver Hinz, Wil M. P. van der Aalst, Christof Weinhardt:
Quantum Computing. Bus. Inf. Syst. Eng. 65(4): 361-367 (2023) - [j277]Wil M. P. van der Aalst, Oliver Hinz, Christof Weinhardt:
Ranking the Ranker: How to Evaluate Institutions, Researchers, Journals, and Conferences? Bus. Inf. Syst. Eng. 65(6): 615-621 (2023) - [j276]Gyunam Park, Daniel Schuster, Wil M. P. van der Aalst:
Pattern-based action engine: Generating process management actions using temporal patterns of process-centric problems. Comput. Ind. 153: 104020 (2023) - [j275]Jan Niklas Adams, Gyunam Park, Wil M. P. van der Aalst:
Preserving complex object-centric graph structures to improve machine learning tasks in process mining. Eng. Appl. Artif. Intell. 125: 106764 (2023) - [j274]Yogesh K. Dwivedi, Nir Kshetri, Laurie Hughes, Emma L. Slade, Anand Jeyaraj, Arpan Kumar Kar, Abdullah M. Baabdullah, Alex Koohang, Vishnupriya Raghavan, Manju Ahuja, Hanaa Albanna, Mousa Ahmad Albashrawi, Adil S. Al-Busaidi, Janarthanan Balakrishnan, Yves Barlette, Sriparna Basu, Indranil Bose, Laurence D. Brooks, Dimitrios Buhalis, Lemuria D. Carter, Soumyadeb Chowdhury, Tom Crick, Scott W. Cunningham, Gareth H. Davies, Robert M. Davison, Rahul De', Denis Dennehy, Yanqing Duan, Rameshwar Dubey, Rohita Dwivedi, John S. Edwards, Carlos Flavián, Robin Gauld, Varun Grover, Mei-Chih Hu, Marijn Janssen, Paul Jones, Iris A. Junglas, Sangeeta Khorana, Sascha Kraus, Kai R. Larsen, Paul Latreille, Sven Laumer, F. Tegwen Malik, Abbas Mardani, Marcello Mariani, Sunil Mithas, Emmanuel Mogaji, Jeretta Horn Nord, Siobhán O'Connor, Fevzi Okumus, Margherita Pagani, Neeraj Pandey, Savvas Papagiannidis, Ilias O. Pappas, Nishith Pathak, Jan Pries-Heje, Ramakrishnan Raman, Nripendra P. Rana, Sven-Volker Rehm, Samuel Ribeiro-Navarrete, Alexander Richter, Frantz Rowe, Suprateek Sarker, Bernd Carsten Stahl, Manoj Kumar Tiwari, Wil M. P. van der Aalst, Viswanath Venkatesh, Giampaolo Viglia, Michael Wade, Paul Walton, Jochen Wirtz, Ryan T. Wright:
Opinion Paper: "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. Int. J. Inf. Manag. 71: 102642 (2023) - [j273]Jan Niklas Adams, Sebastiaan J. van Zelst, Thomas Rose, Wil M. P. van der Aalst:
Explainable concept drift in process mining. Inf. Syst. 114: 102177 (2023) - [j272]Wil M. P. van der Aalst, Riccardo De Masellis, Chiara Di Francescomarino, Chiara Ghidini, Humam Kourani:
Discovering hybrid process models with bounds on time and complexity: When to be formal and when not? Inf. Syst. 116: 102214 (2023) - [j271]Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Performance-preserving event log sampling for predictive monitoring. J. Intell. Inf. Syst. 61(1): 53-82 (2023) - [j270]Luciana Barbieri, Edmundo R. M. Madeira, Kleber Stroeh, Wil M. P. van der Aalst:
A natural language querying interface for process mining. J. Intell. Inf. Syst. 61(1): 113-142 (2023) - [j269]Alessandro Berti, Gyunam Park, Majid Rafiei, Wil M. P. van der Aalst:
A generic approach to extract object-centric event data from databases supporting SAP ERP. J. Intell. Inf. Syst. 61(3): 835-857 (2023) - [j268]Jan Niklas Adams, Cameron Pitsch, Tobias Brockhoff, Wil M. P. van der Aalst:
An Experimental Evaluation of Process Concept Drift Detection. Proc. VLDB Endow. 16(8): 1856-1869 (2023) - [j267]Michael Martini, Daniel Schuster, Wil M. P. van der Aalst:
Mining Frequent Infix Patterns from Concurrency-Aware Process Execution Variants. Proc. VLDB Endow. 16(10): 2666-2678 (2023) - [j266]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Cortado: A dedicated process mining tool for interactive process discovery. SoftwareX 22: 101373 (2023) - [j265]Alessandro Berti, Wil M. P. van der Aalst:
OC-PM: analyzing object-centric event logs and process models. Int. J. Softw. Tools Technol. Transf. 25(1): 1-17 (2023) - [c618]Wil M. P. van der Aalst:
Twin Transitions Powered By Event Data - Using Object-Centric Process Mining To Make Processes Digital and Sustainable. ATAED/PN4TT@Petri Nets 2023 - [c617]Aaron Küsters, Wil M. P. van der Aalst:
Revisiting the Alpha Algorithm To Enable Real-Life Process Discovery Applications. ATAED/PN4TT@Petri Nets 2023 - [c616]Christian Rennert, Lisa Luise Mannel, Wil M. P. van der Aalst:
Improving the eST-Miner Models by Replacing Imprecise Structures Using Place Projection. ATAED/PN4TT@Petri Nets 2023 - [c615]Yisong Zhang, Wil M. P. van der Aalst:
Explorative Process Discovery Using Activity Projections. Petri Nets 2023: 229-239 - [c614]Chiao-Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Event Abstraction for Partial Order Patterns. BPM 2023: 38-54 - [c613]Daniel Schuster, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Incremental Discovery of Process Models Using Trace Fragments. BPM 2023: 55-73 - [c612]Gal Engelberg, Moshe Hadad, Marco Pegoraro, Pnina Soffer, Ethan Hadar, Wil M. P. van der Aalst:
An Uncertainty-Aware Event Log of Network Traffic. BPM (Demos / Resources Forum) 2023: 67-71 - [c611]Wil M. P. van der Aalst:
Experiences from the Internet-of-Production: Using "Data-Models-in-the-Middle" to Fight Complexity and Facilitate Reuse. Business Process Management Workshops 2023: 87-91 - [c610]Timo Pohl, Alessandro Berti, Mahnaz Sadat Qafari, Wil M. P. van der Aalst:
A Collection of Simulated Event Logs for Fairness Assessment in Process Mining. BPM (Demos / Resources Forum) 2023: 87-91 - [c609]Harry H. Beyel, Omar Makke, Oleg Gusikhin, Wil M. P. van der Aalst:
Analyzing Behavior in Cyber-Physical Systems in Connected Vehicles: A Case Study. Business Process Management Workshops 2023: 92-104 - [c608]Zahra Sadeghibogar, Alessandro Berti, Marco Pegoraro, Wil M. P. van der Aalst:
SLURMminer: A Tool for SLURM System Analysis with Process Mining. BPM (Demos / Resources Forum) 2023: 97-101 - [c607]Mohammadreza Fani Sani, Juan J. Garza Gonzalez, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Alignment Approximator: A ProM Plug-In to Approximate Conformance Statistics. BPM (Demos / Resources Forum) 2023: 102-106 - [c606]Eduardo Goulart Rocha, Wil M. P. van der Aalst:
Polynomial-Time Conformance Checking for Process Trees. BPM 2023: 109-125 - [c605]Bianka Bakullari, Jules van Thoor, Dirk Fahland, Wil M. P. van der Aalst:
The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them. BPM (Forum) 2023: 145-162 - [c604]Mahsa Pourbafrani, Niels Lücking, Matthieu Lucke, Wil M. P. van der Aalst:
Steady State Estimation for Business Process Simulations. BPM (Forum) 2023: 178-195 - [c603]Mohammadreza Fani Sani, Martin Kabierski, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Model-Independent Error Bound Estimation for Conformance Checking Approximation. Business Process Management Workshops 2023: 369-382 - [c602]Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study. Business Process Management Workshops 2023: 427-439 - [c601]Jan Niklas Adams, Wil M. P. van der Aalst:
Addressing Convergence, Divergence, and Deficiency Issues. Business Process Management Workshops 2023: 496-507 - [c600]Tsung-Hao Huang, Wil M. P. van der Aalst:
Unblocking Inductive Miner - While Preserving Desirable Properties. BPMDS/EMMSAD@CAiSE 2023: 327-342 - [c599]Wil M. P. van der Aalst:
Learning Colored Petri Nets Using Object-Centric Event Data (OCED2CPN). CiSt 2023: 1-6 - [c598]Chiao-Yun Li, Aparna Joshi, Nicholas T. L. Tam, Sean Shing Fung Lau, Jinhui Huang, Tejaswini Shinde, Wil M. P. van der Aalst:
Rectify Sensor Data in IoT: A Case Study on Enabling Process Mining for Logistic Process in an Air Cargo Terminal. CoopIS 2023: 293-310 - [c597]Harry H. Beyel, Omar Makke, Fangbo Yuan, Oleg Gusikhin, Wil M. P. van der Aalst:
Analyzing Cyber-Physical Systems in Cars: A Case Study. DATA 2023: 195-204 - [c596]Anahita Farhang Ghahfarokhi, Fatemeh Akoochekian, Fareed Zandkarimi, Wil M. P. van der Aalst:
Clustering Object-Centric Event Logs. DATA 2023: 444-451 - [c595]Wil M. P. van der Aalst:
Toward More Realistic Simulation Models Using Object-Centric Process Mining. ECMS 2023: 5-13 - [c594]Mahsa Pourbafrani, Wil M. P. van der Aalst:
Data-Driven Simulation In Process Mining: Introducing A Reference Model. ECMS 2023: 411-420 - [c593]Indira Sen, Dennis Assenmacher, Mattia Samory, Isabelle Augenstein, Wil M. P. van der Aalst, Claudia Wagner:
People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection. EMNLP 2023: 10480-10504 - [c592]Jan Niklas Adams, Jari Peeperkorn, Tobias Brockhoff, Isabelle Terrier, Heiko Göhner, Merih Seran Uysal, Seppe vanden Broucke, Jochen De Weerdt, Wil M. P. van der Aalst:
Discovering high-quality process models despite data scarcity. ER (Companion) 2023 - [c591]Lukas Liss, Jan Niklas Adams, Wil M. P. van der Aalst:
Object-Centric Alignments. ER 2023: 201-219 - [c590]Benedikt Knopp, Mahsa Pourbafrani, Wil M. P. van der Aalst:
Discovering Object-Centric Process Simulation Models. ICPM 2023: 81-88 - [c589]Humam Kourani, Daniel Schuster, Wil M. P. van der Aalst:
Scalable Discovery of Partially Ordered Workflow Models with Formal Guarantees. ICPM 2023: 89-96 - [c588]Majid Rafiei, Duygu Bayrak, Mahsa Pourbafrani, Gyunam Park, Hayyan Helal, Gerhard Lakemeyer, Wil M. P. van der Aalst:
Extracting Rules from Event Data for Study Planning. ICPM Workshops 2023: 361-374 - [c587]Nina Graves, István Koren, Majid Rafiei, Wil M. P. van der Aalst:
From Identities to Quantities: Introducing Items and Decoupling Points to Object-Centric Process Mining. ICPM Workshops 2023: 462-474 - [c586]István Koren, Jan Niklas Adams, Alessandro Berti, Wil M. P. van der Aalst:
OCEL 2.0 Resources - www.ocel-standard.org. ICPM Doctoral Consortium / Demo 2023 - [c585]Christian Rennert, Wil M. P. van der Aalst:
Improving Precision in Process Trees Using Subprocess Tree Logs. ICPM Workshops 2023: 110-122 - [c584]Felix C. Groß, Lisa Luise Mannel, Wil M. P. van der Aalst:
Enhancing the Applicability of the eST-Miner: Efficient Precision-Guided Implicit Place Avoidance. ICPM 2023: 121-128 - [c583]Tian Li, Gyunam Park, Wil M. P. van der Aalst:
Checking Constraints for Object-Centric Process Executions. ICPM Workshops 2023: 392-405 - [c582]Gyunam Park, Sevde Aydin, Cüneyt Ugur, Wil M. P. van der Aalst:
Analyzing an After-Sales Service Process Using Object-Centric Process Mining: A Case Study. ICPM Workshops 2023: 406-418 - [c581]Viki Peeva, Wil M. P. van der Aalst:
Grouping Local Process Models. ICPM Workshops 2023: 419-430 - [c580]