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Sebastiaan J. van Zelst
Person information
- affiliation: Celonis, Germany
- affiliation (former): Fraunhofer Institute for Applied Information Technology, Sankt Augustin, Germany
- affiliation (former): RWTH Aachen University, Germany
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2020 – today
- 2024
- [j21]Daniel Schuster
, Francesca Zerbato
Defining and visualizing process execution variants from partially ordered event data. Inf. Sci. 657: 119958 (2024) - [c61]Eduardo Goulart Rocha
Mining Behavioral Patterns for Conformance Diagnostics. BPM 2024: 291-308 - [c60]Humam Kourani, Sebastiaan J. van Zelst:
POWL: Partially Ordered Workflow Language (Extended Abstract). IJCAI 2024: 8427-8432 - [i20]Gero J. Kolhof, Sebastiaan J. van Zelst:
An Invertible State Space for Process Trees. CoRR abs/2407.21468 (2024) - 2023
- [j20]Jan Niklas Adams
Explainable concept drift in process mining. Inf. Syst. 114: 102177 (2023) - [j19]Mohammadreza Fani Sani
Performance-preserving event log sampling for predictive monitoring. J. Intell. Inf. Syst. 61(1): 53-82 (2023) - [j18]Sander J. J. Leemans, Sebastiaan J. van Zelst, Xixi Lu:
Partial-order-based process mining: a survey and outlook. Knowl. Inf. Syst. 65(1): 1-29 (2023) - [j17]Alessandro Berti, Sebastiaan J. van Zelst, Daniel Schuster
PM4Py: A process mining library for Python. Softw. Impacts 17: 100556 (2023) - [j16]Daniel Schuster
Cortado: A dedicated process mining tool for interactive process discovery. SoftwareX 22: 101373 (2023) - [c59]Chiao-Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Event Abstraction for Partial Order Patterns. BPM 2023: 38-54 - [c58]Daniel Schuster
Incremental Discovery of Process Models Using Trace Fragments. BPM 2023: 55-73 - [c57]Humam Kourani
POWL: Partially Ordered Workflow Language. BPM 2023: 92-108 - [c56]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 - [c55]Sebastiaan J. van Zelst
Context-Based Activity Label-Splitting. BPM 2023: 232-248 - [c54]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 - [c53]Hannes Häfke
Event Data-Driven Feasibility Checking of Process Schedules. CAiSE 2023: 210-225 - [i19]Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro
Performance-Preserving Event Log Sampling for Predictive Monitoring. CoRR abs/2301.07624 (2023) - 2022
- [j15]Gerhardus A. W. M. van Hulzen
Mining context-aware resource profiles in the presence of multitasking. Artif. Intell. Medicine 134: 102434 (2022) - [j14]Daniel Schuster
Utilizing domain knowledge in data-driven process discovery: A literature review. Comput. Ind. 137: 103612 (2022) - [j13]Vincent Bloemen, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones. Inf. Syst. 103: 101456 (2022) - [c52]Humam Kourani
Mining for Long-Term Dependencies in Causal Graphs. Business Process Management Workshops 2022: 117-131 - [c51]Daniel Schuster
Temporal Performance Analysis for Block-Structured Process Models in Cortado. CAiSE Forum 2022: 110-119 - [c50]Daniel Schuster
Conformance Checking for Trace Fragments Using Infix and Postfix Alignments. CoopIS 2022: 299-310 - [c49]Giorgi Lomidze, Daniel Schuster
Enhanced Transformation of BPMN Models with Cancellation Features. EDOC 2022: 128-144 - [c48]Humam Kourani, Sebastiaan J. van Zelst, Barry-Detlef Lehmann, Gabriel Einsdorf, Stefan Helfrich, Fabian Liße:
PM4KNIME: Process Mining Meets the KNIME Analytics Platform (Extended Abstract). ICPM Doctoral Consortium / Demo 2022: 65-69 - [c47]Tian Li
Cache Enhanced Split-Point-Based Alignment Calculation. ICPM 2022: 120-127 - [c46]Daniel Schuster
Control-Flow-Based Querying of Process Executions from Partially Ordered Event Data. ICSOC 2022: 19-35 - [c45]Daniel Schuster
A Generic Trace Ordering Framework for Incremental Process Discovery. IDA 2022: 264-277 - [c44]Chiao-Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
A Framework for Automated Abstraction Class Detection for Event Abstraction. ISDA (2) 2022: 126-136 - [e2]Robert Lorenz, Jan Martijn E. M. van der Werf, Sebastiaan J. van Zelst:
Proceedings of the Workshop on Algorithms & Theories for the Analysis of Event Data co-located with the 43rd International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2022), Bergen, Norway, June 19-24, 2022. CEUR Workshop Proceedings 3167, CEUR-WS.org 2022 [contents] - [e1]Luís Gomes, Paulo Leitão, Robert Lorenz, Jan Martijn E. M. van der Werf, Sebastiaan J. van Zelst:
Joint Proceedings of the Workshop on Algorithms & Theories for the Analysis of Event Data and the International Workshop on Petri Nets for Twin Transition co-located with the 44th International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2023), Caparica, Portugal, June 25-30, 2023. CEUR Workshop Proceedings 3424, CEUR-WS.org 2022 [contents] - [i18]Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, Marco Pegoraro, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Event Log Sampling for Predictive Monitoring. CoRR abs/2204.01470 (2022) - [i17]Daniel Schuster
Conformance Checking for Trace Fragments Using Infix and Postfix Alignments. CoRR abs/2209.04290 (2022) - [i16]Daniel Schuster, Michael Martini, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Control-Flow-Based Querying of Process Executions from Partially Ordered Event Data. CoRR abs/2211.04146 (2022) - 2021
- [j12]Mohammadreza Fani Sani
The impact of biased sampling of event logs on the performance of process discovery. Computing 103(6): 1085-1104 (2021) - [c43]Daniel Schuster
Cortado - An Interactive Tool for Data-Driven Process Discovery and Modeling. Petri Nets 2021: 465-475 - [c42]Agnes Koschmider, Kay Kaczmarek, Mathias Krause, Sebastiaan J. van Zelst:
Demystifying Noise and Outliers in Event Logs: Review and Future Directions. Business Process Management Workshops 2021: 123-135 - [c41]Jan Niklas Adams
A Framework for Explainable Concept Drift Detection in Process Mining. BPM 2021: 400-416 - [c40]Sebastiaan J. van Zelst, Luis F. R. Santos, Wil M. P. van der Aalst:
Data-Driven Process Performance Measurement and Prediction: A Process-Tree-Based Approach. CAiSE Forum 2021: 73-81 - [c39]Daniel Schuster
Freezing Sub-models During Incremental Process Discovery. ER 2021: 14-24 - [c38]Daniel Schuster
Visualizing Trace Variants from Partially Ordered Event Data. ICPM Workshops 2021: 34-46 - [c37]Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani
Event Log Sampling for Predictive Monitoring. ICPM Workshops 2021: 154-166 - [c36]Chiao-Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
An Activity Instance Based Hierarchical Framework for Event Abstraction. ICPM 2021: 160-167 - [i15]Mohammadreza Fani Sani, Martin Kabierski, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Model Independent Error Bound Estimation for Conformance Checking Approximation. CoRR abs/2103.13315 (2021) - [i14]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Cortado - An Interactive Tool for Data-Driven Process Discovery and Modeling. CoRR abs/2105.07666 (2021) - [i13]Jan Niklas Adams, Sebastiaan J. van Zelst, Lara Quack, Kathrin Hausmann, Wil M. P. van der Aalst, Thomas Rose:
A Framework for Explainable Concept Drift Detection in Process Mining. CoRR abs/2105.13155 (2021) - [i12]Wil M. P. van der Aalst, Tobias Brockhoff, Anahita Farhang Ghahfarokhi, Mahsa Pourbafrani, Merih Seran Uysal, Sebastiaan J. van Zelst:
Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP). CoRR abs/2107.13066 (2021) - [i11]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Freezing Sub-Models During Incremental Process Discovery: Extended Version. CoRR abs/2108.00215 (2021) - [i10]Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Visualizing Trace Variants From Partially Ordered Event Data. CoRR abs/2110.02060 (2021) - 2020
- [j11]Sebastiaan J. van Zelst
Translating Workflow Nets to Process Trees: An Algorithmic Approach. Algorithms 13(11): 279 (2020) - [j10]Sebastiaan J. van Zelst, Joos C. A. M. Buijs, Borja Vázquez-Barreiros, Manuel Lama, Manuel Mucientes
Repairing Alignments of Process Models. Bus. Inf. Syst. Eng. 62(4): 289-304 (2020) - [j9]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Improving the performance of process discovery algorithms by instance selection. Comput. Sci. Inf. Syst. 17(3): 927-958 (2020) - [j8]Sebastiaan J. van Zelst, Mohammadreza Fani Sani, Alireza Ostovar, Raffaele Conforti, Marcello La Rosa:
Detection and removal of infrequent behavior from event streams of business processes. Inf. Syst. 90: 101451 (2020) - [j7]Niek Tax
An interdisciplinary comparison of sequence modeling methods for next-element prediction. Softw. Syst. Model. 19(6): 1345-1365 (2020) - [c35]Mahsa Pourbafrani
Supporting Automatic System Dynamics Model Generation for Simulation in the Context of Process Mining. BIS 2020: 249-263 - [c34]Daniel Schuster
Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm. BPM 2020: 147-164 - [c33]Sebastiaan J. van Zelst, Yukun Cao:
A Generic Framework for Attribute-Driven Hierarchical Trace Clustering. Business Process Management Workshops 2020: 308-320 - [c32]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Conformance Checking Approximation Using Subset Selection and Edit Distance. CAiSE 2020: 234-251 - [c31]Wil M. P. van der Aalst, Tobias Brockhoff, Anahita Farhang Ghahfarokhi, Mahsa Pourbafrani
Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP). DATA (Revised Selected Papers) 2020: 1-31 - [c30]Mahsa Pourbafrani
Semi-automated Time-Granularity Detection for Data-Driven Simulation Using Process Mining and System Dynamics. ER 2020: 77-91 - [c29]Dominik Janssen
Process Model Discovery from Sensor Event Data. ICPM Workshops 2020: 69-81 - [c28]Mohammadreza Fani Sani, Juan J. Garza Gonzalez, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Conformance Checking Approximation Using Simulation. ICPM 2020: 105-112 - [c27]Sander J. J. Leemans
Using Multi-Level Information in Hierarchical Process Mining: Balancing Behavioural Quality and Model Complexity. ICPM 2020: 137-144 - [c26]Daniel Schuster
Alignment Approximation for Process Trees. ICPM Workshops 2020: 247-259 - [c25]Chiao-Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Stage-Based Process Performance Analysis. ICSOC Workshops 2020: 349-364 - [c24]Mahsa Pourbafrani
Supporting Decisions in Production Line Processes by Combining Process Mining and System Dynamics. IHSI 2020: 461-467 - [c23]Daniel Schuster
Incremental Discovery of Hierarchical Process Models. RCIS 2020: 417-433 - [i9]Daniel Schuster, Sebastiaan J. van Zelst:
Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm. CoRR abs/2002.05945 (2020) - [i8]Sebastiaan J. van Zelst:
Translating Workflow Nets to Process Trees: An Algorithmic Approach. CoRR abs/2004.08213 (2020) - [i7]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Alignment Approximation for Process Trees. CoRR abs/2009.14094 (2020)
2010 – 2019
- 2019
- [j6]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Repairing Outlier Behaviour in Event Logs using Contextual Behaviour. Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model. 14: 5:1-5:24 (2019) - [j5]Sebastiaan J. van Zelst
Online conformance checking: relating event streams to process models using prefix-alignments. Int. J. Data Sci. Anal. 8(3): 269-284 (2019) - [j4]Marwan Hassani
On the application of sequential pattern mining primitives to process discovery: Overview, outlook and opportunity identification. WIREs Data Mining Knowl. Discov. 9(6) (2019) - [c22]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
The Impact of Event Log Subset Selection on the Performance of Process Discovery Algorithms. ADBIS (Short Papers and Workshops) 2019: 391-404 - [c21]Mohammadreza Fani Sani, Alessandro Berti, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Filtering Toolkit: Interactively Filter Event Logs to Improve the Quality of Discovered Models. BPM (PhD/Demos) 2019: 134-138 - [c20]Alessandro Berti, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
PM4Py Web Services: Easy Development, Integration and Deployment of Process Mining Features in any Application Stack. BPM (PhD/Demos) 2019: 174-178 - [c19]Chiao-Yun Li, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
A Generic Approach for Process Performance Analysis Using Bipartite Graph Matching. Business Process Management Workshops 2019: 199-211 - [c18]Junxiong Gao, Sebastiaan J. van Zelst, Xixi Lu, Wil M. P. van der Aalst
Automated Robotic Process Automation: A Self-Learning Approach. OTM Conferences 2019: 95-112 - [c17]Mahsa Pourbafrani
Scenario-Based Prediction of Business Processes Using System Dynamics. OTM Conferences 2019: 422-439 - [i6]Alessandro Berti, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Process Mining for Python (PM4Py): Bridging the Gap Between Process- and Data Science. CoRR abs/1905.06169 (2019) - [i5]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Conformance Checking Approximation using Subset Selection and Edit Distance. CoRR abs/1912.05022 (2019) - 2018
- [j3]Sebastiaan J. van Zelst
Discovering workflow nets using integer linear programming. Computing 100(5): 529-556 (2018) - [j2]Sebastiaan J. van Zelst
Event stream-based process discovery using abstract representations. Knowl. Inf. Syst. 54(2): 407-435 (2018) - [j1]Sebastiaan J. van Zelst, Alfredo Bolt, Boudewijn F. van Dongen:
Computing Alignments of Event Data and Process Models. Trans. Petri Nets Other Model. Concurr. 13: 1-26 (2018) - [c16]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Repairing Outlier Behaviour in Event Logs. BIS 2018: 115-131 - [c15]Vincent Bloemen, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Maximizing Synchronization for Aligning Observed and Modelled Behaviour. BPM 2018: 233-249 - [c14]Andrea Burattin
Online Conformance Checking Using Behavioural Patterns. BPM 2018: 250-267 - [c13]Sebastiaan J. van Zelst, Mohammadreza Fani Sani, Alireza Ostovar, Raffaele Conforti, Marcello La Rosa:
Filtering Spurious Events from Event Streams of Business Processes. CAiSE 2018: 35-52 - [c12]Niek Tax
An Experimental Evaluation of the Generalizing Capabilities of Process Discovery Techniques and Black-Box Sequence Models. BPMDS/EMMSAD@CAiSE 2018: 165-180 - [c11]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Applying Sequence Mining for Outlier Detection in Process Mining. OTM Conferences (2) 2018: 98-116 - [i4]Niek Tax, Irene Teinemaa, Sebastiaan J. van Zelst:
An Interdisciplinary Comparison of Sequence Modeling Methods for Next-Element Prediction. CoRR abs/1811.00062 (2018) - 2017
- [c10]Sebastiaan J. van Zelst, Alfredo Bolt, Boudewijn F. van Dongen:
Tuning Alignment Computation: An Experimental Evaluation. ATAED@Petri Nets/ACSD 2017: 6-20 - [c9]Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Improving Process Discovery Results by Filtering Outliers Using Conditional Behavioural Probabilities. Business Process Management Workshops 2017: 216-229 - [i3]Wil M. P. van der Aalst
RapidProM: Mine Your Processes and Not Just Your Data. CoRR abs/1703.03740 (2017) - [i2]Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst, H. M. W. Verbeek:
Discovering Relaxed Sound Workflow Nets using Integer Linear Programming. CoRR abs/1703.06733 (2017) - [i1]Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst:
Event Stream-Based Process Discovery using Abstract Representations. CoRR abs/1704.08101 (2017) - 2016
- [c8]Borja Vázquez-Barreiros, Sebastiaan J. van Zelst, Joos C. A. M. Buijs, Manuel Lama
Repairing Alignments: Striking the Right Nerve. BMMDS/EMMSAD 2016: 266-281 - [c7]Sebastiaan J. van Zelst, Boudewijn F. van Dongen
Online Discovery of Cooperative Structures in Business Processes. OTM Conferences 2016: 210-228 - 2015
- [c6]Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst:
ILP-Based Process Discovery Using Hybrid Regions. ATAED@Petri Nets/ACSD 2015: 47-61 - [c5]Sergio Hernández, Joaquin Ezpeleta
Assessing Process Discovery Scalability in Data Intensive Environments. BDC 2015: 99-104 - [c4]Sergio Hernández, Sebastiaan J. van Zelst, Joaquín Ezpeleta, Wil M. P. van der Aalst:
Handling Big(ger) Logs: Connecting ProM 6 to Apache Hadoop. BPM (Demos) 2015: 80-84 - [c3]Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst:
Know What You Stream: Generating Event Streams from CPN Models in ProM 6. BPM (Demos) 2015: 85-89 - [c2]Sebastiaan J. van Zelst, Boudewijn F. van Dongen
Avoiding Over-Fitting in ILP-Based Process Discovery. BPM 2015: 163-171 - 2014
- [c1]Sebastiaan J. van Zelst, Andrea Burattin, Boudewijn F. van Dongen, H. M. W. Verbeek:
Data Streams in ProM 6: A Single-node Architecture. BPM (Demos) 2014: 81
Coauthor Index
[j21] [c61] [j20] [j19] [j16] [c59] [c58] [c56] [c54] [i19] [j14] [j13] [c52] [c51] [c50] [c46] [c45] [c44] [i18] [i17] [i16] [j12] [c43] [c41] [c40] [c39] [c38] [c37] [c36] [i15] [i14] [i13] [i12] [i11] [i10] [j9] [c35] [c32] [c31] [c30] [c28] [c26] [c25] [c24] [c23] [i7] [j6] [j5] [j4] [c22] [c21] [c20] [c19] [c18] [c17] [i6] [i5] [j3] [j2] [c16] [c15] [c11] [c9] [i3] [i2] [i1] [c7] [c6] [c5] [c4] [c3] [c2]
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