Sebastiaan van Zelst - Google Scholar Citations

Cited by

	All	Since 2015
Citations	306	306
h-index	10	10
i10-index	10	10

140

105

2015201620172018201920205 24 40 97 133 7

Co-authors

Wil van der AalstRWTH Aachen UniversityVerified email at pads.rwth-aachen.de
Boudewijn van DongenProfessor of Computer Science, Eindhoven University of TechnologyVerified email at tue.nl
MohammadReza Fani SaniPhD candidateVerified email at pads.rwth-aachen.de
Alfredo BoltEindhoven University of TechnologyVerified email at tue.nl
Eric VerbeekScientific Engineer, Eindhoven University of TechnologyVerified email at tue.nl
Marwan HassaniAssistant Professor of Computer Science at TU/eVerified email at tue.nl
Ezpeleta JoaquínZaragozaVerified email at unizar.es
Niek TaxBooking.comVerified email at booking.com
Andrea BurattinAssociate Professor, Technical University of DenmarkVerified email at dtu.dk
Alessandro BertiPADS RWTHVerified email at pads.rwth-aachen.de
Borja Vázquez BarreirosPhD, Alumni from CiTIUS, Universidade de Santiago de Compostela (USC)Verified email at usc.es
Manuel MucientesUniversity of Santiago de Compostela (Spain)Verified email at usc.es
Manuel LamaCiTIUS, University of Santiago de CompostelaVerified email at usc.es
Joos Buijsformer Assistant professor, Eindhoven University of TechnologyVerified email at tue.nl
Irene TeinemaaData Scientist at Booking.comVerified email at booking.com
Alireza OstovarProcess DiamondVerified email at processdiamond.com
Raffaele ConfortiDirector & Co-founder of Process DiamondVerified email at processdiamond.com
Marcello La RosaSchool of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Vincent BloemenUniversity of TwenteVerified email at utwente.nl
Jaco van de PolProfessor of Computer Science, Aarhus UniversityVerified email at cs.au.dk

Sebastiaan van Zelst

Fraunhofer FIT & RWTH Aachen University

Verified email at fit.fraunhofer.de - Homepage

Process Mining Data Mining Artificial Intelligence


Title	Cited by	Year
RapidProM: mine your processes and not just your data WMP van der Aalst, A Bolt, SJ van Zelst arXiv preprint arXiv:1703.03740, 2017	34	2017
Avoiding over-fitting in ILP-based process discovery SJ van Zelst, BF van Dongen, WMP van der Aalst International conference on business process management, 163-171, 2016	27	2016
Online conformance checking: relating event streams to process models using prefix-alignments SJ van Zelst, A Bolt, M Hassani, BF van Dongen, WMP van der Aalst International Journal of Data Science and Analytics 8 (3), 269-284, 2019	26	2019
Event stream-based process discovery using abstract representations SJ van Zelst, BF van Dongen, WMP van der Aalst Knowledge and Information Systems, 2017	22	2017
ILP-Based Process Discovery Using Hybrid Regions. SJ van Zelst, BF van Dongen, WMP van der Aalst ATAED@ petri nets/ACSD, 47-61, 2015	22	2015
Discovering workflow nets using integer linear programming SJ van Zelst, BF van Dongen, WMP van der Aalst, HMW Verbeek Computing 100 (5), 529-556, 2018	19	2018
Improving process discovery results by filtering outliers using conditional behavioural probabilities MF Sani, SJ van Zelst, WMP van der Aalst International Conference on Business Process Management, 216-229, 2017	17	2017
Handling big (ger) logs: Connecting prom 6 to apache hadoop S Hernández, WMP Van der Aalst, SJ Van Zelst, J Ezpeleta CEUR workshop proc., 2015	17	2015
Know What You Stream: Generating Event Streams from CPN Models in ProM 6. SJ van Zelst, BF van Dongen, WMP van der Aalst BPM (Demos), 85-89, 2015	10	2015
Data Streams in ProM 6: A Single-node Architecture. SJ van Zelst, A Burattin, BF van Dongen, HMW (Eric) Verbeek BPM (Demos), 81, 2014	10	2014
An interdisciplinary comparison of sequence modeling methods for next-element prediction N Tax, I Teinemaa, SJ van Zelst arXiv preprint arXiv:1811.00062, 2018	9	2018
Filtering spurious events from event streams of business processes SJ van Zelst, MF Sani, A Ostovar, R Conforti, M La Rosa International Conference on Advanced Information Systems Engineering, 35-52, 2018	9	2018
Tuning Alignment Computation: An Experimental Evaluation SJ van Zelst, A Bolt, BF van Dongen ATAED, 2017	9	2017
Process mining for Python (PM4Py): bridging the gap between process-and data science A Berti, SJ van Zelst, W van der Aalst arXiv preprint arXiv:1905.06169, 2019	8	2019
Maximizing synchronization for aligning observed and modelled behaviour V Bloemen, SJ van Zelst, WMP van der Aalst, BF van Dongen, ... International Conference on Business Process Management, 233-249, 2018	8	2018
Online conformance checking using behavioural patterns A Burattin, SJ van Zelst, A Armas-Cervantes, BF van Dongen, J Carmona International Conference on Business Process Management, 250-267, 2018	8	2018
Repairing outlier behaviour in event logs MF Sani, SJ van Zelst, WMP van der Aalst International Conference on Business Information Systems, 115-131, 2018	8	2018
Online discovery of cooperative structures in business processes SJ van Zelst, BF van Dongen, WMP van der Aalst OTM Confederated International Conferences" On the Move to Meaningful …, 2016	8	2016
Assessing process discovery scalability in data intensive environments S Hernández, J Ezpeleta, SJ van Zelst, WMP van der Aalst 2015 IEEE/ACM 2nd International Symposium on Big Data Computing (BDC), 99-104, 2015	7	2015
Applying sequence mining for outlier detection in process mining MF Sani, SJ van Zelst, WMP van der Aalst OTM Confederated International Conferences" On the Move to Meaningful …, 2018	6	2018

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Upload PDF

Follow this author

Cited by

Co-authors