Niek Tax

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Wil van der AalstProfessor of Process and Data Science, RWTH Aachen University || Celonis || Fraunhofer FIT || TU/eVerified email at pads.rwth-aachen.de
Natalia SidorovaTechnische Universiteit EindhovenVerified email at tue.nl
Marlon DumasProfessor at University of Tartu | Chief Product Officer at ApromoreVerified email at ut.ee
Irene TeinemaaDeepMindVerified email at deepmind.com
Ilya VerenichSchool of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Marcello La RosaProfessor at University of Melbourne | Chief Executive Officer at ApromoreVerified email at unimelb.edu.au
Massimiliano de LeoniAssociate Professor of Computer Science, University of PadovaVerified email at math.unipd.it
Djoerd HiemstraRadboud UniversityVerified email at cs.ru.nl
Fabrizio MaggiAssociate Professor, Free University of Bozen-BolzanoVerified email at ut.ee
Sebastiaan van ZelstCelonisVerified email at celonis.com
Emin AlasgarovChief Data Officer, Unibank. Adjunct Instructor, ADA UniversityVerified email at ada.edu.az
Benjamin DALMASResearcherVerified email at crim.ca
Ido GuyResearch Scientist ManagerVerified email at meta.com
Dirk FahlandAssociate Professor in Computer Science, Eindhoven University of TechnologyVerified email at tue.nl
Xixi LuAssistant Professor at Utrecht UniversityVerified email at uu.nl
Sander J.J. LeemansRWTH Aachen UniversityVerified email at bpm.rwth-aachen.de
Matthias WeidlichHumboldt-Universität zu BerlinVerified email at hu-berlin.de
Stephan A. Fahrenkrog-PetersenWeizenbaum Institute for the Networked SocietyVerified email at hu-berlin.de
Felix MannhardtAssistant Professor Eindhoven University of TechnologyVerified email at tue.nl
Nicola ZannoneEindhoven University of TechnologyVerified email at tue.nl

Niek Tax

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Machine Learning Sequence Models Data Mining Pattern Mining Process Mining


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Predictive business process monitoring with LSTM neural networks N Tax, I Verenich, M La Rosa, M Dumas Proceedings of the International Conference on Advanced Information Systems …, 2017	637	2017
Mining local process models N Tax, N Sidorova, R Haakma, WMP van der Aalst Journal of Innovation in Digital Ecosystems 3 (2), 183-196, 2016	153	2016
Event abstraction for process mining using supervised learning techniques N Tax, N Sidorova, R Haakma, WMP van der Aalst Proceedings of the SAI Intelligent Systems Conference, 2016	129	2016
A cross-benchmark comparison of 87 learning to rank methods N Tax, S Bockting, D Hiemstra Information processing & management 51 (6), 757-772, 2015	120	2015
Discovering More Precise Process Models from Event Logs by Filtering Out Chaotic Activities N Tax, N Sidorova, WMP van der Aalst Journal of Intelligent Information Systems, 1-33, 2017	112	2017
Predicting The Dutch Football Competition Using Public Data: A Machine Learning Approach N Tax, Y Joustra 2014, 2014	93	2014
The Imprecisions of Precision Measures in Process Mining N Tax, X Lu, N Sidorova, D Fahland, WMP van der Aalst Information Processing Letters 135, 1-8, 2018	90	2018
An interdisciplinary comparison of sequence modeling methods for next-element prediction N Tax, I Teinemaa, SJ van Zelst Software and Systems Modeling 19 (6), 1345-1365, 2020	69	2020
Evaluating conformance measures in process mining using conformance propositions AF Syring, N Tax, WMP van der Aalst Transactions on Petri Nets and Other Models of Concurrency XIV, 192-221, 2019	66	2019
Alarm-based prescriptive process monitoring I Teinemaa, N Tax, M de Leoni, M Dumas, FM Maggi Business Process Management Forum: BPM Forum 2018, Sydney, NSW, Australia …, 2018	63	2018
Fire now, fire later: alarm-based systems for prescriptive process monitoring SA Fahrenkrog-Petersen, N Tax, I Teinemaa, M Dumas, M de Leoni, ... Knowledge and Information Systems, 2021	58	2021
Human Activity Prediction in Smart Home Environments with LSTM Neural Networks N Tax Proceedings of the International Conference on Intelligent Environments, 2018	57	2018
Unsupervised Event Abstraction using Pattern Abstraction and Local Process Models F Mannhardt, N Tax International Working Conference on Business Process Modeling, Development …, 2017	53	2017
Mining Process Model Descriptions of Daily Life through Event Abstraction N Tax, N Sidorova, R Haakma, WMP van der Aalst Intelligent Systems and Applications 751, 2017	46	2017
Heuristic approaches for generating local process models through log projections N Tax, N Sidorova, WMP van der Aalst, R Haakma Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2016	37	2016
Interest-Driven Discovery of Local Process Models N Tax, B Dalmas, N Sidorova, WMP van der Aalst, S Norre Information Systems, 2018	25	2018
Generating Time-Based Label Refinements to Discover More Precise Process Models N Tax, E Alasgarov, N Sidorova, R Haakma, WMP van der Aalst Journal of Ambient Intelligence and Smart Environments 11 (2), 165-182, 2019	23	2019
Explaining Predictive Uncertainty with Information Theoretic Shapley Values DS Watson, J O'Hara, N Tax, R Mudd, I Guy Advances in Neural Information Processing Systems 37, 2023	20	2023
Machine learning for fraud detection in e-Commerce: A research agenda N Tax, KJ de Vries, M de Jong, N Dosoula, B van den Akker, J Smith, ... Deployable Machine Learning for Security Defense: Second International …, 2021	20	2021
Causal reasoning over control-flow decisions in process models SJJ Leemans, N Tax International Conference on Advanced Information Systems Engineering, 183-200, 2022	19	2022

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