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ORCIDSebastiaan 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, 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)- [c61]Eduardo Goulart Rocha, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Sebastiaan J. van Zelst, Thomas Rose, Wil M. P. van der Aalst:
Explainable concept drift in process mining. Inf. Syst. 114: 102177 (2023) - [j19]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) - [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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Incremental Discovery of Process Models Using Trace Fragments. BPM 2023: 55-73 - [c57]Humam Kourani, Sebastiaan J. van Zelst:
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, Jonas Tai, Moritz Langenberg, Xixi Lu:
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, Sebastiaan J. van Zelst:
Event Data-Driven Feasibility Checking of Process Schedules. CAiSE 2023: 210-225 - [i19]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. CoRR abs/2301.07624 (2023) - 2022
- [j15]Gerhardus A. W. M. van Hulzen, Chiao-Yun Li, Niels Martin, Sebastiaan J. van Zelst, Benoît Depaire:
Mining context-aware resource profiles in the presence of multitasking. Artif. Intell. Medicine 134: 102434 (2022) - [j14]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Boudewijn F. van Dongen, Jaco van de Pol:
Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones. Inf. Syst. 103: 101456 (2022) - [c52]Humam Kourani, Chiara Di Francescomarino, Chiara Ghidini, Wil M. P. van der Aalst, Sebastiaan J. van Zelst:
Mining for Long-Term Dependencies in Causal Graphs. Business Process Management Workshops 2022: 117-131 - [c51]Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Temporal Performance Analysis for Block-Structured Process Models in Cortado. CAiSE Forum 2022: 110-119 - [c50]Daniel Schuster, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Conformance Checking for Trace Fragments Using Infix and Postfix Alignments. CoopIS 2022: 299-310 - [c49]Giorgi Lomidze, Daniel Schuster, Chiao-Yun Li, Sebastiaan J. van Zelst:
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, Sebastiaan J. van Zelst:
Cache Enhanced Split-Point-Based Alignment Calculation. ICPM 2022: 120-127 - [c46]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. ICSOC 2022: 19-35 - [c45]Daniel Schuster, Emanuel Domnitsch, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
The impact of biased sampling of event logs on the performance of process discovery. Computing 103(6): 1085-1104 (2021) - [c43]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, 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. 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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Freezing Sub-models During Incremental Process Discovery. ER 2021: 14-24 - [c38]Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Visualizing Trace Variants from Partially Ordered Event Data. ICPM Workshops 2021: 34-46 - [c37]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. 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, Sander J. J. Leemans:
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, Irene Teinemaa, Sebastiaan J. van Zelst:
An interdisciplinary comparison of sequence modeling methods for next-element prediction. Softw. Syst. Model. 19(6): 1345-1365 (2020) - [c35]Mahsa Pourbafrani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Supporting Automatic System Dynamics Model Generation for Simulation in the Context of Process Mining. BIS 2020: 249-263 - [c34]Daniel Schuster, Sebastiaan J. van Zelst:
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, Merih Seran Uysal, Sebastiaan J. van Zelst:
Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP). DATA (Revised Selected Papers) 2020: 1-31 - [c30]Mahsa Pourbafrani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Semi-automated Time-Granularity Detection for Data-Driven Simulation Using Process Mining and System Dynamics. ER 2020: 77-91 - [c29]Dominik Janssen, Felix Mannhardt, Agnes Koschmider, Sebastiaan J. van Zelst:
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, Kanika Goel, Sebastiaan J. van Zelst:
Using Multi-Level Information in Hierarchical Process Mining: Balancing Behavioural Quality and Model Complexity. ICPM 2020: 137-144 - [c26]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Supporting Decisions in Production Line Processes by Combining Process Mining and System Dynamics. IHSI 2020: 461-467 - [c23]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Alfredo Bolt, Marwan Hassani, Boudewijn F. van Dongen, Wil M. P. van der Aalst:
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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Boudewijn F. van Dongen, Wil M. P. van der Aalst, H. M. W. Verbeek:
Discovering workflow nets using integer linear programming. Computing 100(5): 529-556 (2018) - [j2]Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst:
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, Boudewijn F. van Dongen, Jaco van de Pol:
Maximizing Synchronization for Aligning Observed and Modelled Behaviour. BPM 2018: 233-249 - [c14]Andrea Burattin, Sebastiaan J. van Zelst, Abel Armas-Cervantes, Boudewijn F. van Dongen, Josep Carmona:
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, Sebastiaan J. van Zelst, Irene Teinemaa:
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, Alfredo Bolt, Sebastiaan J. van Zelst:
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, Manuel Mucientes:
Repairing Alignments: Striking the Right Nerve. BMMDS/EMMSAD 2016: 266-281 - [c7]Sebastiaan J. van Zelst, Boudewijn F. van Dongen, Wil M. P. van der Aalst:
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, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
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, Wil M. P. van der Aalst:
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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