Wil M. P. van der Aalst - researchr alias

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Viewing Publication 1 - 100 from 982

2025

2024

Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World ApplicationDaniel Schuster 0001, Elisabetta Benevento, Davide Aloini, Wil M. P. van der Aalst. jhir, 8(3):523-554, September 2024. [doi]

Defining and visualizing process execution variants from partially ordered event dataDaniel Schuster 0001, Francesca Zerbato, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. isci, 657:119958, February 2024. [doi]

Super VariantsJan Niklas Adams, Emilie Hastrup-Kiil, Gyunam Park, Wil M. P. van der Aalst. BPM 2024: 111-128 [doi]

Improving Predictive Process Monitoring Using Object-Centric Process MiningJan Niklas Adams, Hannes Drescher, Andreas Swoboda, Nikou Günnemann, Gyunam Park, Wil M. P. van der Aalst. ecis 2024: [doi]

CSV-PM-LLM-Parsing: Automatic Ingestion of CSV Event Logs for Process Mining using LLMsAlessandro Berti, Wil M. P. van der Aalst. BPM 2024: 131-135 [doi]

Explainable Object-Centric Anomaly Detection: the Role of Domain KnowledgeAlessandro Berti, Urszula Jessen, Wil M. P. van der Aalst, Dirk Fahland. BPM 2024: 162-168 [doi]

Graph-based feature extraction on object-centric event logsAlessandro Berti, Johannes Herforth, Mahnaz Sadat Qafari, Wil M. P. van der Aalst. ijdsa, 18(2):139-155, August 2024. [doi]

Improving Process Discovery Using Translucent Activity RelationshipsHarry H. Beyel, Wil M. P. van der Aalst. BPM 2024: 146-163 [doi]

Process-Aware Analysis of Treatment Paths in Heart Failure Patients: A Case StudyHarry H. Beyel, Marlo Verket, Viki Peeva, Christian Rennert, Marco Pegoraro 0001, Katharina Schütt, Wil M. P. van der Aalst, Nikolaus Marx. biostec 2024: 506-515 [doi]

ActivityGen: Extracting Enabled Activities from ScreenshotsHarry H. Beyel, Sovin Manuel, Wil M. P. van der Aalst. ecai 2024: 712-720 [doi]

Translucent Precision: Exploiting Enabling Information to Evaluate the Quality of Process ModelsHarry Herbert Beyel, Wil M. P. van der Aalst. rcis 2024: 29-37 [doi]

Analyzing Data Streams from Cyber-Physical-Systems: A Case StudyHarry H. Beyel, Omar Makke, Mahsa Pourbafrani, Oleg Gusikhin, Wil M. P. van der Aalst. sncs, 5(6):706, August 2024. [doi]

Process Comparison Using Petri Net DecompositionTobias Brockhoff, Moritz Nicolas Gose, Merih Seran Uysal, Wil M. P. van der Aalst. apn 2024: 83-105 [doi]

Process Comparison Based on Selection-Projection StructuresTobias Brockhoff, Merih Seran Uysal, Wil M. P. van der Aalst. caise 2024: 20-35 [doi]

Wasserstein Weight Estimation for Stochastic Petri NetsTobias Brockhoff, Merih Seran Uysal, Wil M. P. van der Aalst. icpm 2024: 81-88 [doi]

A chance for models to show their quality: Stochastic process model-log dimensionsAdam T. Burke, Sander J. J. Leemans, Moe Thandar Wynn, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede. is, 124:102382, 2024. [doi]

Tuning Machine Learning to Address Process Mining RequirementsPaolo Ceravolo, Sylvio Barbon Junior, Ernesto Damiani, Wil M. P. van der Aalst. access, 12:24583-24595, 2024. [doi]

Maximizing Reuse and Interoperability in Industry 4.0 with a Minimal Data Exchange Format for Machine DataLeah Tacke genannt Unterberg, István Koren, Wil M. P. van der Aalst. modellierung 2024: 103-118 [doi]

The Internet of Value: Unleashing the Blockchain's Potential with TokenizationBjörn Hanneke, Oliver Hinz, Jella Pfeiffer, Wil M. P. van der Aalst. bise, 66(4):411-419, August 2024. [doi]

A Pipeline for the Usage of the Core Data Set of the Medical Informatics Initiative for Process Mining - A Technical Case ReportHauke Heidemeyer, Leo Auhagen, Raphael W. Majeed, Marco Pegoraro 0001, Jonas Bienzeisler, Viki Peeva, Harry H. Beyel, Rainer Röhrig, Wil M. P. van der Aalst, Behrus Puladi. gmds 2024: 30-39 [doi]

ProReco: A Process Discovery Recommender SystemTsung-Hao Huang, Tarek Junied, Marco Pegoraro, Wil M. P. van der Aalst. caise 2024: 93-101 [doi]

Fast & Sound: Accelerating Synthesis-Rules-Based Process DiscoveryTsung-Hao Huang, Enzo Schneider, Marco Pegoraro 0001, Wil M. P. van der Aalst. BPMDS 2024: 259-274 [doi]

Navigating the Data Model Divide in Smart Manufacturing: An Empirical Investigation for Enhanced AI IntegrationIstván Koren, Matthias Jarke, Judith Michael, Malte Heithoff, Leah Tacke genannt Unterberg, Max Stachon, Bernhard Rumpe, Wil M. P. van der Aalst. BPMDS 2024: 275-290 [doi]

Process Modeling with Large Language ModelsHumam Kourani, Alessandro Berti, Daniel Schuster 0001, Wil M. P. van der Aalst. BPMDS 2024: 229-244 [doi]

ProMoAI: Process Modeling with Generative AIHumam Kourani, Alessandro Berti, Daniel Schuster 0001, Wil M. P. van der Aalst. IJCAI 2024: 8708-8712 [doi]

Overstock Problems in a Purchase-to-Pay Process: An Object-Centric Process Mining Case StudyDina Kretzschmann, Gyunam Park, Alessandro Berti, Wil M. P. van der Aalst. caise 2024: 347-359 [doi]

ProM4Py - A Python Wrapper For The ProM FrameworkHenrik Kämmerling, Eduardo Goulart Rocha, Wil M. P. van der Aalst. icpm 2024: [doi]

Rust4PM: A Versatile Process Mining Library for When Performance MattersAaron Küsters, Wil M. P. van der Aalst. BPM 2024: 91-95 [doi]

TOTeM: Temporal Object Type Model for Object-Centric Process MiningLukas Liss, Jan Niklas Adams, Wil M. P. van der Aalst. BPM 2024: 107-123 [doi]

Discovering Process Models with Long-Term Dependencies while Providing Guarantees and Filtering Infrequent Behavior PatternsLisa Luise Mannel, Wil M. P. van der Aalst. FUIN, 190(2-4):109-158, 2024. [doi]

Process Variant Analysis Across Continuous Features: A Novel FrameworkAli Norouzifar, Majid Rafiei, Marcus Dees, Wil M. P. van der Aalst. BPMDS 2024: 129-142 [doi]

Imposing Rules in Process Discovery: An Inductive Mining ApproachAli Norouzifar, Marcus Dees, Wil M. P. van der Aalst. rcis 2024: 220-236 [doi]

Bridging Domain Knowledge and Process Discovery Using Large Language ModelsAli Norouzifar, Humam Kourani, Marcus Dees, Wil M. P. van der Aalst. BPM 2025: 44-56 [doi]

Incorporating Behavioral Recommendations Mined from Event Logs into AI PlanningGyunam Park, Majid Rafiei, Hayyan Helal, Gerhard Lakemeyer, Wil M. P. van der Aalst. caise 2024: 20-28 [doi]

Conformance Checking and Performance Analysis Using Object-Centric Directly-Follows GraphsGyunam Park, Jan Niklas Adams, Wil M. P. van der Aalst. BPM 2024: 179-196 [doi]

New Laws and RegulationJella Pfeiffer, Jens F. Lachenmaier, Oliver Hinz, Wil M. P. van der Aalst. bise, 66(6):653-666, December 2024. [doi]

Stochastic Conformance Checking Based on Expected Subtrace FrequencyEduardo Goulart Rocha, Sander J. J. Leemans, Wil M. P. van der Aalst. icpm 2024: 73-80 [doi]

Mining Behavioral Patterns for Conformance DiagnosticsEduardo Goulart Rocha, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. BPM 2024: 291-308 [doi]

Precision-Guided Minimization of Arbitrary Declarative Process ModelsEduardo Goulart Rocha, Wil M. P. van der Aalst. BPMDS 2024: 48-56 [doi]

Applying Process Mining on Scientific Workflows: A Case Study on High Performance Computing DataZahra Sadeghibogar, Alessandro Berti, Marco Pegoraro 0001, Wil M. P. van der Aalst. BPM 2025: 84-96 [doi]

Process Tree AlignmentsChristopher T. Schwanen, Wied Pakusa, Wil M. P. van der Aalst. edoc 2025: 300-317 [doi]

Lifting Process Discovery and Conformance Checking to the Next Level: A General Approach to Object-Centric Process Mining (Invited Talk)Wil M. P. van der Aalst. apn 2024: 1-12 [doi]

Matthias Jarke (1952-2024), A Pioneer in Information Systems and Data ManagementWil M. P. van der Aalst. bise, 66(2):135, April 2024. [doi]

Digital Democracy: A Wake-Up CallChristof Weinhardt, Jonas Fegert, Oliver Hinz, Wil M. P. van der Aalst. bise, 66(2):127-134, April 2024. [doi]

The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs]Moe Thandar Wynn, Wil M. P. van der Aalst, Eric Verbeek 0001, Bruno N. Di Stefano. cim, 19(1):20-23, February 2024. [doi]

2023

Incremental Discovery of Process Models Using Trace FragmentsDaniel Schuster 0001, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. BPM 2023: 55-73 [doi]

Cortado: A dedicated process mining tool for interactive process discoveryDaniel Schuster 0001, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. softx, 22:101373, May 2023. [doi]

Discovering high-quality process models despite data scarcityJan 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. ER 2024: [doi]

Addressing Convergence, Divergence, and Deficiency IssuesJan Niklas Adams, Wil M. P. van der Aalst. BPM 2024: 496-507 [doi]

Preserving complex object-centric graph structures to improve machine learning tasks in process miningJan Niklas Adams, Gyunam Park, Wil M. P. van der Aalst. eaai, 125:106764, 2023. [doi]

The Interplay Between High-Level Problems and the Process Instances that Give Rise to ThemBianka Bakullari, Jules van Thoor, Dirk Fahland, Wil M. P. van der Aalst. BPM 2023: 145-162 [doi]

A natural language querying interface for process miningLuciana Barbieri, Edmundo R. M. Madeira, Kleber Stroeh, Wil M. P. van der Aalst. jiis, 61(1):113-142, August 2023. [doi]

Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case StudyAlessandro Berti, Daniel Schuster 0001, Wil M. P. van der Aalst. BPM 2024: 427-439 [doi]

OC-PM: analyzing object-centric event logs and process modelsAlessandro Berti, Wil M. P. van der Aalst. STTT, 25(1):1-17, February 2023. [doi]

Analyzing Cyber-Physical Systems in Cars: A Case StudyHarry H. Beyel, Omar Makke, Fangbo Yuan, Oleg Gusikhin, Wil M. P. van der Aalst. data 2023: 195-204 [doi]

Analyzing Behavior in Cyber-Physical Systems in Connected Vehicles: A Case StudyHarry H. Beyel, Omar Makke, Oleg Gusikhin, Wil M. P. van der Aalst. BPM 2024: 92-104 [doi]

An Uncertainty-Aware Event Log of Network TrafficGal Engelberg, Moshe Hadad, Marco Pegoraro 0001, Pnina Soffer, Ethan Hadar, Wil M. P. van der Aalst. BPM 2023: 67-71 [doi]

Clustering Object-Centric Event LogsAnahita Farhang Ghahfarokhi, Fatemeh Akoochekian, Fareed Zandkarimi, Wil M. P. van der Aalst. data 2023: 444-451 [doi]

From Identities to Quantities: Introducing Items and Decoupling Points to Object-Centric Process MiningNina Graves, István Koren, Majid Rafiei, Wil M. P. van der Aalst. icpm 2024: 462-474 [doi]

ReThink Your Processes! A Review of Process Mining for SustainabilityNina Graves, István Koren, Wil M. P. van der Aalst. ict4s 2023: 164-175 [doi]

Enhancing the Applicability of the eST-Miner: Efficient Precision-Guided Implicit Place AvoidanceFelix C. Groß, Lisa Luise Mannel, Wil M. P. van der Aalst. icpm 2023: 121-128 [doi]

Unblocking Inductive Miner - While Preserving Desirable PropertiesTsung-Hao Huang, Wil M. P. van der Aalst. BPMDS 2023: 327-342 [doi]

Discovering Object-Centric Process Simulation ModelsBenedikt Knopp, Mahsa Pourbafrani, Wil M. P. van der Aalst. icpm 2023: 81-88 [doi]

OCEL 2.0 Resources - www.ocel-standard.orgIstván Koren, Jan Niklas Adams, Alessandro Berti, Wil M. P. van der Aalst. icpm 2024: [doi]

Scalable Discovery of Partially Ordered Workflow Models with Formal GuaranteesHumam Kourani, Daniel Schuster 0001, Wil M. P. van der Aalst. icpm 2023: 89-96 [doi]

Revisiting the Alpha Algorithm To Enable Real-Life Process Discovery ApplicationsAaron Küsters, Wil M. P. van der Aalst. apn 2022: [doi]

Checking Constraints for Object-Centric Process ExecutionsTian Li, Gyunam Park, Wil M. P. van der Aalst. icpm 2024: 392-405 [doi]

Rectify Sensor Data in IoT: A Case Study on Enabling Process Mining for Logistic Process in an Air Cargo TerminalChiao Yun Li, Aparna Joshi, Nicholas T. L. Tam, Sean Shing Fung Lau, Jinhui Huang, Tejaswini Shinde, Wil M. P. van der Aalst. coopis 2024: 293-310 [doi]

Unveiling Bottlenecks in Logistics: A Case Study on Process Mining for Root Cause Identification and Diagnostics in an Air Cargo TerminalChiao Yun Li, Tejaswini Shinde, Wanyi He, Sean Shing Fung Lau, Morgan Xian Biao Hiew, Nicholas T. L. Tam, Aparna Joshi, Wil M. P. van der Aalst. icsoc 2023: 291-307 [doi]

Event Abstraction for Partial Order PatternsChiao Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. BPM 2023: 38-54 [doi]

Object-Centric AlignmentsLukas Liss, Jan Niklas Adams, Wil M. P. van der Aalst. ER 2023: 201-219 [doi]

Quantum ComputingMichael Nofer, Kevin Bauer, Oliver Hinz, Wil M. P. van der Aalst, Christof Weinhardt. bise, 65(4):361-367, August 2023. [doi]

Discovering Process Models that Support Desired Behavior and Avoid Undesired BehaviorAli Norouzifar, Wil M. P. van der Aalst. SAC 2023: 365-368 [doi]

Analyzing an After-Sales Service Process Using Object-Centric Process Mining: A Case StudyGyunam Park, Sevde Aydin, Cüneyt Ugur, Wil M. P. van der Aalst. icpm 2024: 406-418 [doi]

Pattern-based action engine: Generating process management actions using temporal patterns of process-centric problemsGyunam Park, Daniel Schuster 0001, Wil M. P. van der Aalst. cii, 153:104020, December 2023. [doi]

Grouping Local Process ModelsViki Peeva, Wil M. P. van der Aalst. icpm 2024: 419-430 [doi]

A Collection of Simulated Event Logs for Fairness Assessment in Process MiningTimo Pohl, Alessandro Berti, Mahnaz Sadat Qafari, Wil M. P. van der Aalst. BPM 2023: 87-91 [doi]

Data-Driven Simulation In Process Mining: Introducing A Reference ModelMahsa Pourbafrani, Wil M. P. van der Aalst. ecms 2023: 411-420 [doi]

Steady State Estimation for Business Process SimulationsMahsa Pourbafrani, Niels Lücking, Matthieu Lucke, Wil M. P. van der Aalst. BPM 2023: 178-195 [doi]

Extracting Rules from Event Data for Study PlanningMajid Rafiei, Duygu Bayrak, Mahsa Pourbafrani, Gyunam Park, Hayyan Helal, Gerhard Lakemeyer, Wil M. P. van der Aalst. icpm 2024: 361-374 [doi]

TraVaG: Differentially Private Trace Variant Generation Using GANsMajid Rafiei, Frederik Wangelik, Mahsa Pourbafrani, Wil M. P. van der Aalst. rcis 2023: 415-431 [doi]

An Abstraction-Based Approach for Privacy-Aware Federated Process MiningMajid Rafiei, Wil M. P. van der Aalst. access, 11:33697-33714, 2023. [doi]

Improving Precision in Process Trees Using Subprocess Tree LogsChristian Rennert, Wil M. P. van der Aalst. icpm 2024: 110-122 [doi]

Improving the eST-Miner Models by Replacing Imprecise Structures Using Place ProjectionChristian Rennert, Lisa Luise Mannel, Wil M. P. van der Aalst. apn 2022: [doi]

Polynomial-Time Conformance Checking for Process TreesEduardo Goulart Rocha, Wil M. P. van der Aalst. BPM 2023: 109-125 [doi]

SLURMminer: A Tool for SLURM System Analysis with Process MiningZahra Sadeghibogar, Alessandro Berti, Marco Pegoraro 0001, Wil M. P. van der Aalst. BPM 2023: 97-101 [doi]

Alignment Approximator: A ProM Plug-In to Approximate Conformance StatisticsMohammadreza Fani Sani, Juan J. Garza Gonzalez, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. BPM 2023: 102-106 [doi]

Model-Independent Error Bound Estimation for Conformance Checking ApproximationMohammadreza Fani Sani, Martin Kabierski, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. BPM 2024: 369-382 [doi]

Welcome to the Era of ChatGPT et alTimm Teubner, Christoph M. Flath, Christof Weinhardt, Wil M. P. van der Aalst, Oliver Hinz. bise, 65(2):95-101, 2023. [doi]

Experiences from the Internet-of-Production: Using "Data-Models-in-the-Middle" to Fight Complexity and Facilitate ReuseWil M. P. van der Aalst. BPM 2024: 87-91 [doi]

Toward More Realistic Simulation Models Using Object-Centric Process MiningWil M. P. van der Aalst. ecms 2023: 5-13 [doi]

Twin Transitions Powered By Event Data - Using Object-Centric Process Mining To Make Processes Digital and SustainableWil M. P. van der Aalst. apn 2022: [doi]

Learning Colored Petri Nets Using Object-Centric Event Data (OCED2CPN)Wil M. P. van der Aalst. cist 2023: 1-6 [doi]

Ranking the Ranker: How to Evaluate Institutions, Researchers, Journals, and Conferences?Wil M. P. van der Aalst, Oliver Hinz, Christof Weinhardt. bise, 65(6):615-621, December 2023. [doi]

Explorative Process Discovery Using Activity ProjectionsYisong Zhang, Wil M. P. van der Aalst. apn 2023: 229-239 [doi]

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