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Sander J. J. Leemans

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affiliation: RWTH Aachen University, Germany

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2020 – today

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2024
[j23]
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Adam Banham, Arthur H. M. ter Hofstede, Sander J. J. Leemans, Felix Mannhardt, Robert Andrews, Moe Thandar Wynn:
Comparing Conformance Checking for Decision Mining: An Axiomatic Approach. IEEE Access 12: 60276-60298 (2024)
[j22]
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Jan Pennekamp, Roman Matzutt, Christopher Klinkmüller, Lennart Bader, Martin Serror, Eric Wagner, Sidra Malik, Maria Spiß, Jessica Rahn, Tan Gürpinar, Eduard Vlad, Sander J. J. Leemans, Salil S. Kanhere, Volker Stich, Klaus Wehrle:
An Interdisciplinary Survey on Information Flows in Supply Chains. ACM Comput. Surv. 56(2): 32:1-32:38 (2024)
[j21]
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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)
[j20]
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Sander J. J. Leemans, Fabrizio Maria Maggi, Marco Montali:
Enjoy the silence: Analysis of stochastic Petri nets with silent transitions. Inf. Syst. 124: 102383 (2024)
[j19]
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Andreas Egger, Arthur H. M. ter Hofstede, Wolfgang Kratsch, Sander J. J. Leemans, Maximilian Röglinger, Moe Thandar Wynn:
Bot log mining: An approach to the integrated analysis of Robotic Process Automation and process mining. Inf. Syst. 126: 102431 (2024)
[c50]
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Jan Niklas van Detten, Pol Schumacher, Sander J. J. Leemans:
Object Synchronizations and Specializations with Silent Objects in Object-Centric Petri Nets. BPM 2024: 57-74
[c49]
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Sander J. J. Leemans, Tian Li, Marco Montali, Artem Polyvyanyy:
Stochastic Process Discovery: Can It Be Done Optimally? CAiSE 2024: 36-52
[c48]
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Sander J. J. Leemans, Tian Li, Jan Niklas van Detten:
Ebi - a Stochastic Process Mining Framework. ICPM Doctoral Consortium / Demo 2024
[c47]
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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
[c46]
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Jan Niklas van Detten, Pol Schumacher, Sander J. J. Leemans:
Discovering Compact, Live and Identifier-Sound Object-Centric Process Models. ICPM 2024: 113-120
[e2]
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Adela del-Río-Ortega, Marco Montali, Stefanie Rinderle-Ma, Hajo A. Reijers, Jan vom Brocke, Mathias Weske, Benoît Depaire, Marta Indulska, Han van der Aa, Weronika T. Adrian, Laura Genga, Sander J. J. Leemans, Katarzyna Gdowska, María Teresa Gómez-López, Jana-Rebecca Rehse, Simone Agostinelli:
Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Forum at BPM 2024 co-located with 22nd International Conference on Business Process Management (BPM 2024), Krakow, Poland, September 1st to 6th, 2024. CEUR Workshop Proceedings 3758, CEUR-WS.org 2024 [contents]
[i4]
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  - journals/corr/abs-2401-01022
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Jan Pennekamp, Roman Matzutt, Christopher Klinkmüller, Lennart Bader, Martin Serror, Eric Wagner, Sidra Malik, Maria Spiß, Jessica Rahn, Tan Gürpinar, Eduard Vlad, Sander J. J. Leemans, Salil S. Kanhere, Volker Stich, Klaus Wehrle:
An Interdisciplinary Survey on Information Flows in Supply Chains. CoRR abs/2401.01022 (2024)
2023
[j18]
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Sander J. J. Leemans, Andrew Partington, Jonathan Karnon, Moe Thandar Wynn:
Process mining for healthcare decision analytics with micro-costing estimations. Artif. Intell. Medicine 135: 102473 (2023)
[j17]
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Azumah Mamudu, Wasana Bandara, Sander J. J. Leemans, Moe Thandar Wynn:
A process mining impacts framework. Bus. Process. Manag. J. 29(3): 690-709 (2023)
[j16]
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Sander J. J. Leemans, Artem Polyvyanyy:
Stochastic-aware precision and recall measures for conformance checking in process mining. Inf. Syst. 115: 102197 (2023)
[j15]
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Sander J. J. Leemans, Lisa Luise Mannel, Natalia Sidorova:
Significant stochastic dependencies in process models. Inf. Syst. 118: 102223 (2023)
[j14]
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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)
[j13]
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Sander J. J. Leemans, James M. McGree, Artem Polyvyanyy, Arthur H. M. ter Hofstede:
Statistical Tests and Association Measures for Business Processes. IEEE Trans. Knowl. Data Eng. 35(7): 7497-7511 (2023)
[c45]
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  - conf/apn/MannhardtLSL23
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Felix Mannhardt, Sander J. J. Leemans, Christopher T. Schwanen, Massimiliano de Leoni:
Modelling Data-Aware Stochastic Processes - Discovery and Conformance Checking. Petri Nets 2023: 77-98
[c44]
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Massimiliano de Leoni, Francesco Vinci, Sander J. J. Leemans, Felix Mannhardt:
Investigating the Influence of Data-Aware Process States on Activity Probabilities in Simulation Models: Does Accuracy Improve? BPM 2023: 129-145
[c43]
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Tabib Ibne Mazhar, Asad Tariq, Sander J. J. Leemans, Kanika Goel, Moe Thandar Wynn, Andrew Staib:
Stochastic-Aware Comparative Process Mining in Healthcare. BPM 2023: 341-358
[c42]
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Kanika Goel, Sareh Sadeghianasl, Robert Andrews, Arthur H. M. ter Hofstede, Moe Wynn, Dakshi Kapugama Geeganage, Sander J. J. Leemans, James M. McGree, Rebekah Eden, Andrew Staib, Rob Eley, Raelene Donovan:
Digital Health Data Imperfection Patterns and Their Manifestations in an Australian Digital Hospital. HICSS 2023: 3235-3244
[c41]
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Adam T. Burke, Sander J. J. Leemans, Moe Thandar Wynn, Cameron D. Campbell:
State Snapshot Process Discovery on Career Paths of Qing Dynasty Civil Servants. ICPM 2023: 73-80
[c40]
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Jan Niklas van Detten, Pol Schumacher, Sander J. J. Leemans:
An Approximate Inductive Miner. ICPM 2023: 129-136
[c39]
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Sander J. J. Leemans, Fabrizio Maria Maggi, Marco Montali:
Finite-Trace Analysis of Stochastic Systems with Silent Transitions (Extended Abstract). IJCAI 2023: 6452-6457
[i3]
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  - journals/corr/abs-2306-06376
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Sander J. J. Leemans, Fabrizio Maria Maggi, Marco Montali:
Enjoy the Silence: Analysis of Stochastic Petri Nets with Silent Transitions. CoRR abs/2306.06376 (2023)
2022
[b1]
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Sander J. J. Leemans:
Robust Process Mining with Guarantees - Process Discovery, Conformance Checking and Enhancement. Lecture Notes in Business Information Processing 440, Springer 2022, ISBN 978-3-030-96654-6, pp. 1-459
[j12]
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Adam Banham, Sander J. J. Leemans, Moe Thandar Wynn, Robert Andrews, Kevin B. Laupland, Lucy Shinners:
xPM: Enhancing exogenous data visibility. Artif. Intell. Medicine 133: 102409 (2022)
[j11]
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Tobias Fehrer, Dominik Andreas Fischer, Sander J. J. Leemans, Maximilian Röglinger, Moe Thandar Wynn:
An assisted approach to business process redesign. Decis. Support Syst. 156: 113749 (2022)
[j10]
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Kanika Goel, Sander J. J. Leemans, Niels Martin, Moe Thandar Wynn:
Quality-Informed Process Mining: A Case for Standardised Data Quality Annotations. ACM Trans. Knowl. Discov. Data 16(5): 97:1-97:47 (2022)
[c38]
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Simon, Meena Jha, Sander J. J. Leemans, Regina Berretta, Ayse Aysin Bilgin, Lakmali Jayarathna, Judy Sheard:
Online Assessment and COVID: Opportunities and Challenges. ACE 2022: 27-35
[c37]
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Sander J. J. Leemans:
Leveraging Frequencies in Event Data a Pledge for Stochastic Process Mining. ATAED@Petri Nets 2022: 1-8
[c36]
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Tobias Fehrer, Dominik Andreas Fischer, Sander J. J. Leemans, Maximilian Röglinger, Moe Thandar Wynn:
A Tool for Assisted Business Process Redesign. BPM (PhD/Demos) 2022: 97-101
[c35]
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Benoît Depaire, Gert Janssenswillen, Sander J. J. Leemans:
Alpha Precision: Estimating the Significant System Behavior in a Model. BPM (Forum) 2022: 120-136
[c34]
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Azumah Mamudu, Wasana Bandara, Moe Thandar Wynn, Sander J. J. Leemans:
A Process Mining Success Factors Model. BPM 2022: 143-160
[c33]
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Sander J. J. Leemans, Fabrizio Maria Maggi, Marco Montali:
Reasoning on Labelled Petri Nets and Their Dynamics in a Stochastic Setting. BPM 2022: 324-342
[c32]
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Sander J. J. Leemans, Niek Tax:
Causal Reasoning over Control-Flow Decisions in Process Models. CAiSE 2022: 183-200
[c31]
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Sander J. J. Leemans:
FilterTree: a Repeatable Branching XES Editor (Extended Abstract). ICPM Doctoral Consortium / Demo 2022: 70-74
[c30]
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Adam T. Burke, Sander J. J. Leemans, Moe Thandar Wynn, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede:
Stochastic Process Model-Log Quality Dimensions: An Experimental Study. ICPM 2022: 80-87
[i2]
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  - journals/corr/abs-2203-10410
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Sander J. J. Leemans:
Language-Preserving Reduction Rules for Block-Structured Workflow Nets. CoRR abs/2203.10410 (2022)
2021
[j9]
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Niels Martin, Dominik Andreas Fischer, Georgi Dimov Kerpedzhiev, Kanika Goel, Sander J. J. Leemans, Maximilian Röglinger, Wil M. P. van der Aalst, Marlon Dumas, Marcello La Rosa, Moe Thandar Wynn:
Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study. Bus. Inf. Syst. Eng. 63(5): 511-527 (2021)
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Sander J. J. Leemans, Wil M. P. van der Aalst, Tobias Brockhoff, Artem Polyvyanyy:
Stochastic process mining: Earth movers' stochastic conformance. Inf. Syst. 102: 101724 (2021)
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Adriano Augusto, Marlon Dumas, Marcello La Rosa, Sander J. J. Leemans, Seppe K. L. M. vanden Broucke:
Optimization framework for DFG-based automated process discovery approaches. Softw. Syst. Model. 20(4): 1245-1270 (2021)
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Adam Burke, Sander J. J. Leemans, Moe Thandar Wynn:
Discovering Stochastic Process Models by Reduction and Abstraction. Petri Nets 2021: 312-336
[c28]
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Kanika Goel, Sander J. J. Leemans, Moe Thandar Wynn, Arthur H. M. ter Hofstede, Janne Barnes:
Improving PhD Student Journeys: Insights from an Australian Higher Education Institution. BPM Industry Forum 2021: 27-38
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Rebekah Eden, Rehan Syed, Sander J. J. Leemans, Joos A. C. M. Buijs:
A Case Study of Inconsistency in Process Mining Use: Implications for the Theory of Effective Use. BPM 2021: 363-379
[c26]
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Adam Banham, Sander J. J. Leemans, Moe Thandar Wynn, Robert Andrews:
xPM: A Framework for Process Mining with Exogenous Data. ICPM Workshops 2021: 85-97
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Sander J. J. Leemans, Henrik Leopold:
Process Mining Workshops - ICPM 2020 International Workshops, Padua, Italy, October 5-8, 2020, Revised Selected Papers. Lecture Notes in Business Information Processing 406, Springer 2021, ISBN 978-3-030-72692-8 [contents]
2020
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Sebastiaan J. van Zelst, Sander J. J. Leemans:
Translating Workflow Nets to Process Trees: An Algorithmic Approach. Algorithms 13(11): 279 (2020)
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Rehan Syed, Suriadi Suriadi, Michael Adams, Wasana Bandara, Sander J. J. Leemans, Chun Ouyang, Arthur H. M. ter Hofstede, Inge van de Weerd, Moe Thandar Wynn, Hajo A. Reijers:
Robotic Process Automation: Contemporary themes and challenges. Comput. Ind. 115: 103162 (2020)
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Sander J. J. Leemans, Dirk Fahland:
Information-preserving abstractions of event data in process mining. Knowl. Inf. Syst. 62(3): 1143-1197 (2020)
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Alireza Ostovar, Sander J. J. Leemans, Marcello La Rosa:
Robust Drift Characterization from Event Streams of Business Processes. ACM Trans. Knowl. Discov. Data 14(3): 30:1-30:57 (2020)
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Shiva Shabaninejad, Hassan Khosravi, Sander J. J. Leemans, Shazia W. Sadiq, Marta Indulska:
Recommending Insightful Drill-Downs Based on Learning Processes for Learning Analytics Dashboards. AIED (1) 2020: 486-499
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Rehan Syed, Sander J. J. Leemans, Rebekah Eden, Joos A. C. M. Buijs:
Process Mining Adoption - A Technology Continuity Versus Discontinuity Perspective. BPM (Forum) 2020: 229-245
[c23]
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Sander J. J. Leemans, Artem Polyvyanyy:
Stochastic-Aware Conformance Checking: An Entropy-Based Approach. CAiSE 2020: 217-233
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Andreas Egger, Arthur H. M. ter Hofstede, Wolfgang Kratsch, Sander J. J. Leemans, Maximilian Röglinger, Moe Thandar Wynn:
Bot Log Mining: Using Logs from Robotic Process Automation for Process Mining. ER 2020: 51-61
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Sander J. J. Leemans, Shiva Shabaninejad, Kanika Goel, Hassan Khosravi, Shazia W. Sadiq, Moe Thandar Wynn:
Identifying Cohorts: Recommending Drill-Downs Based on Differences in Behaviour for Process Mining. ER 2020: 92-102
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Sander J. J. Leemans, Shiva Shabaninejad, Kanika Goel, Hassan Khosravi, Shazia W. Sadiq, Moe Thandar Wynn:
Identifying Cohorts that Differ in their Behaviour: Tool Support. ER Forum/Posters/Demos 2020: 163-167
[c19]
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Wasana Bandara, Mythreyi Velmurugan, Sander J. J. Leemans:
Building 'holistic' Business process modelling skills for IS graduates. ICIS 2020
[c18]
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Artem Polyvyanyy, Hanan Alkhammash, Claudio Di Ciccio, Luciano García-Bañuelos, Anna A. Kalenkova, Sander J. J. Leemans, Jan Mendling, Alistair Moffat, Matthias Weidlich:
Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining. ICPM Doctoral Consortium / Tools 2020: 39-42
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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
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Adam Burke, Sander J. J. Leemans, Moe Thandar Wynn:
Stochastic Process Discovery by Weight Estimation. ICPM Workshops 2020: 260-272
[c15]
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Alifah Syamsiyah, Sander J. J. Leemans:
Process discovery using in-database minimum self distance abstractions. SAC 2020: 26-35
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Artem Polyvyanyy, Hanan Alkhammash, Claudio Di Ciccio, Luciano García-Bañuelos, Anna A. Kalenkova, Sander J. J. Leemans, Jan Mendling, Alistair Moffat, Matthias Weidlich:
Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining. CoRR abs/2008.09558 (2020)

2010 – 2019

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2019
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Sander J. J. Leemans, Anja F. Syring, Wil M. P. van der Aalst:
Earth Movers' Stochastic Conformance Checking. BPM Forum 2019: 127-143
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Sander J. J. Leemans, Erik Poppe, Moe Thandar Wynn:
Directly Follows-Based Process Mining: Exploration & a Case Study. ICPM 2019: 25-32
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Sander J. J. Leemans:
Automated Process Discovery. Encyclopedia of Big Data Technologies 2019
2018
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Scalable process discovery and conformance checking. Softw. Syst. Model. 17(2): 599-631 (2018)
[c12]
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Sander J. J. Leemans:
Robust Process Mining with Guarantees. BPM (Dissertation/Demos/Industry) 2018: 46-50
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Sander J. J. Leemans, Niek Tax, Arthur H. M. ter Hofstede:
Indulpet Miner: Combining Discovery Algorithms. OTM Conferences (1) 2018: 97-115
2015
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Arik Senderovich, Sander J. J. Leemans, Shahar Harel, Avigdor Gal, Avishai Mandelbaum, Wil M. P. van der Aalst:
Discovering Queues from Event Logs with Varying Levels of Information. Business Process Management Workshops 2015: 154-166
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Using Life Cycle Information in Process Discovery. Business Process Management Workshops 2015: 204-217
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Scalable Process Discovery with Guarantees. BMMDS/EMMSAD 2015: 85-101
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Maikel L. van Eck, Xixi Lu, Sander J. J. Leemans, Wil M. P. van der Aalst:
PM ^2 : A Process Mining Project Methodology. CAiSE 2015: 297-313
2014
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Discovering Block-Structured Process Models from Incomplete Event Logs. Petri Nets 2014: 91-110
[c5]
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Process and Deviation Exploration with Inductive Visual Miner. BPM (Demos) 2014: 46
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Exploring Processes and Deviations. Business Process Management Workshops 2014: 304-316
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Sander J. J. Leemans:
Process Discovery and Exploration. Business Process Management Workshops 2014: 582-585
2013
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Yi-Ling Hwong, Jeroen J. A. Keiren, Vincent J. J. Kusters, Sander J. J. Leemans, Tim A. C. Willemse:
Formalising and analysing the control software of the Compact Muon Solenoid Experiment at the Large Hadron Collider. Sci. Comput. Program. 78(12): 2435-2452 (2013)
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Discovering Block-Structured Process Models from Event Logs - A Constructive Approach. Petri Nets 2013: 311-329
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Sander J. J. Leemans, Dirk Fahland, Wil M. P. van der Aalst:
Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour. Business Process Management Workshops 2013: 66-78

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