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Viewing Publication 1 - 100 from 936

2024

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]

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]

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]

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]

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]

An Experimental Evaluation of Process Concept Drift DetectionJan Niklas Adams, Cameron Pitsch, Tobias Brockhoff, Wil M. P. van der Aalst. pvldb, 16(8):1856-1869, 2023. [doi]

Explainable concept drift in process miningJan Niklas Adams, Sebastiaan J. van Zelst, Thomas Rose 0001, Wil M. P. van der Aalst. is, 114:102177, March 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]

A generic approach to extract object-centric event data from databases supporting SAP ERPAlessandro Berti, Gyunam Park, Majid Rafiei, Wil M. P. van der Aalst. jiis, 61(3):835-857, December 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]

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

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]

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]

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

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

Mining Frequent Infix Patterns from Concurrency-Aware Process Execution VariantsMichael Martini, Daniel Schuster 0001, Wil M. P. van der Aalst. pvldb, 16(10):2666-2678, 2023. [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]

Performance-preserving event log sampling for predictive monitoringMohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro 0001, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. jiis, 61(1):53-82, August 2023. [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]

Discovering hybrid process models with bounds on time and complexity: When to be formal and when not?Wil M. P. van der Aalst, Riccardo De Masellis, Chiara Di Francescomarino, Chiara Ghidini, Humam Kourani. is, 116:102214, June 2023. [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]

Sustainable Systems EngineeringWil M. P. van der Aalst, Oliver Hinz, Christof Weinhardt. bise, 65(1):1-6, February 2023. [doi]

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

2022

Uncertain Case Identifiers in Process Mining: A User Study of the Event-Case Correlation Problem on Click DataMarco Pegoraro 0001, Merih Seran Uysal, Tom-Hendrik Hülsmann, Wil M. P. van der Aalst. BPMDS 2022: 173-187 [doi]

A Framework for Extracting and Encoding Features from Object-Centric Event DataJan Niklas Adams, Gyunam Park, Sergej Levich, Daniel Schuster, Wil M. P. van der Aalst. icsoc 2022: 36-53 [doi]

OCπ: Object-Centric Process InsightsJan Niklas Adams, Wil M. P. van der Aalst. apn 2022: 139-150 [doi]

ocpa: A Python library for object-centric process analysisJan Niklas Adams, Gyunam Park, Wil M. P. van der Aalst. simpa, 14:100438, December 2022. [doi]

High-Level Event Mining: A FrameworkBianka Bakullari, Wil M. P. van der Aalst. icpm 2022: 136-143 [doi]

Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case Study - Case StudyElisabetta Benevento, Marco Pegoraro 0001, Mattia Antoniazzi, Harry H. Beyel, Viki Peeva, Paul Balfanz, Wil M. P. van der Aalst, Lukas Martin, Gernot Marx. icpm 2023: 315-327 [doi]

PM4Py-GPU: A High-Performance General-Purpose Library for Process MiningAlessandro Berti, Minh Phan Nghia, Wil M. P. van der Aalst. rcis 2022: 727-734 [doi]

Creating Translucent Event Logs to Improve Process DiscoveryHarry H. Beyel, Wil M. P. van der Aalst. icpm 2023: 435-447 [doi]

Modeling Digital Shadows in Manufacturing by Using Process MiningTobias Brockhoff, Merih Seran Uysal, Wil M. P. van der Aalst. modellierung 2022: 133-138 [doi]

Stochastic Process Model-Log Quality Dimensions: An Experimental StudyAdam Burke, Sander J. J. Leemans, Moe Thandar Wynn, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede. icpm 2022: 80-87 [doi]

Data-Aware Process Oriented Query LanguageEduardo González López de Murillas, Hajo A. Reijers, Wil M. P. van der Aalst. In Artem Polyvyanyy, editor, Process Querying Methods. pages 49-83, Springer, 2022. [doi]

Enhancing Data-Awareness of Object-Centric Event LogsAlexandre Goossens, Johannes De Smedt, Jan Vanthienen, Wil M. P. van der Aalst. icpm 2023: 18-30 [doi]

Discovering Sound Free-Choice Workflow Nets with Non-block StructuresTsung-Hao Huang, Wil M. P. van der Aalst. edoc 2022: 200-216 [doi]

Comparing Ordering Strategies for Process Discovery Using Synthesis RulesTsung-Hao Huang, Wil M. P. van der Aalst. icsoc 2023: 40-52 [doi]

Detecting Surprising Situations in Event DataChristian Kohlschmidt, Mahnaz Sadat Qafari, Wil M. P. van der Aalst. icpm 2023: 216-228 [doi]

Mining for Long-Term Dependencies in Causal GraphsHumam Kourani, Chiara Di Francescomarino, Chiara Ghidini, Wil M. P. van der Aalst, Sebastiaan J. van Zelst. BPM 2023: 117-131 [doi]

A Framework for Automated Abstraction Class Detection for Event AbstractionChiao Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. isda 2023: 126-136 [doi]

Discovering Process Models with Long-Term Dependencies While Providing Guarantees and Handling Infrequent BehaviorLisa Luise Mannel, Wil M. P. van der Aalst. apn 2022: 303-324 [doi]

OPerA: Object-Centric Performance AnalysisGyunam Park, Jan Niklas Adams, Wil M. P. van der Aalst. ER 2022: 281-292 [doi]

Explainable Predictive Decision Mining for Operational SupportGyunam Park, Aaron Küsters, Mara Tews, Cameron Pitsch, Jonathan Schneider, Wil M. P. van der Aalst. icsoc 2023: 66-79 [doi]

Monitoring Constraints in Business Processes Using Object-Centric Constraint GraphsGyunam Park, Wil M. P. van der Aalst. icpm 2023: 479-492 [doi]

Analyzing Process-Aware Information System Updates Using Digital Twins of OrganizationsGyunam Park, Marco Comuzzi, Wil M. P. van der Aalst. rcis 2022: 159-176 [doi]

Detecting Context-Aware Deviations in Process ExecutionsGyunam Park, Janik-Vasily Benzin, Wil M. P. van der Aalst. BPM 2022: 190-206 [doi]

From Place Nets to Local Process ModelsViki Peeva, Lisa Luise Mannel, Wil M. P. van der Aalst. apn 2022: 346-368 [doi]

Discrimination-Aware Process Mining: A DiscussionTimo Pohl, Mahnaz Sadat Qafari, Wil M. P. van der Aalst. icpm 2023: 101-113 [doi]

Hybrid Business Process Simulation: Updating Detailed Process Simulation Models Using High-Level SimulationsMahsa Pourbafrani, Wil M. P. van der Aalst. rcis 2022: 177-194 [doi]

A Tool for Business Processes DiagnosticsMahsa Pourbafrani, Firas Gharbi, Wil M. P. van der Aalst. icsoc 2023: 350-354 [doi]

Process Diagnostics at Coarse-grained LevelsMahsa Pourbafrani, Firas Gharbi, Wil M. P. van der Aalst. ICEIS 2022: 484-491 [doi]

Temporal Performance Analysis for Block-Structured Process Models in CortadoDaniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. caise 2022: 110-119 [doi]

A Generic Trace Ordering Framework for Incremental Process DiscoveryDaniel Schuster, Emanuel Domnitsch, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. ida 2022: 264-277 [doi]

Conformance Checking for Trace Fragments Using Infix and Postfix AlignmentsDaniel Schuster, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. coopis 2022: 299-310 [doi]

Control-Flow-Based Querying of Process Executions from Partially Ordered Event DataDaniel Schuster, Michael Martini, Sebastiaan J. van Zelst, Wil M. P. van der Aalst. icsoc 2022: 19-35 [doi]

BISE StudentAli Sunyaev, Christof Weinhardt, Wil M. P. van der Aalst, Oliver Hinz. bise, 64(6):701-706, 2022. [doi]

Scaling Process Mining to Turn Insights into ActionsWil M. P. van der Aalst, Josep Carmona 0001. In Wil M. P. van der Aalst, Josep Carmona 0001, editors, Process Mining Handbook. Volume 448 of Lecture Notes in Business Information Processing, pages 495-502, Springer, 2022. [doi]

Foundations of Process DiscoveryWil M. P. van der Aalst. In Wil M. P. van der Aalst, Josep Carmona 0001, editors, Process Mining Handbook. Volume 448 of Lecture Notes in Business Information Processing, pages 37-75, Springer, 2022. [doi]

Process Mining: A 360 Degree OverviewWil M. P. van der Aalst. In Wil M. P. van der Aalst, Josep Carmona 0001, editors, Process Mining Handbook. Volume 448 of Lecture Notes in Business Information Processing, pages 3-34, Springer, 2022. [doi]

Discovering Directly-Follows Complete Petri Nets from Event DataWil M. P. van der Aalst. BIRTHDAY 2022: 539-558 [doi]

European leadership in process managementWil M. P. van der Aalst. CACM, 65(4):80-83, 2022. [doi]

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