Niek Tax - Google Scholar Citations

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	All	Since 2014
Citations	390	387
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Co-authors

Natalia SidorovaTechnische Universiteit EindhovenVerified email at tue.nl
Wil van der AalstRWTH Aachen UniversityVerified email at pads.rwth-aachen.de
Marlon DumasUniversity of TartuVerified email at ut.ee
Ilya VerenichSchool of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Marcello La RosaSchool of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Djoerd HiemstraUniversity of TwenteVerified email at cs.utwente.nl
Irene TeinemaaData Scientist at Booking.comVerified email at booking.com
Benjamin DALMASAssistant ProfessorVerified email at emse.fr
Xixi LuPostdoctoral Researcher at Utrecht UniversityVerified email at uu.nl
Emin AlasgarovLecturer of Computer and Information Sciences, ADA UniversityVerified email at ada.edu.az
Sebastiaan van ZelstFraunhofer Institute for Applied Information Technology (FIT)/ RWTH Aachen UniversityVerified email at pads.rwth-aachen.de
Dirk FahlandAssistant Professor in Computer Science, Eindhoven University of TechnologyVerified email at tue.nl
Fabrizio MaggiAssociate Professor, University of TartuVerified email at ut.ee
Massimiliano de LeoniAssistant Professor of Computer Science, University of PadovaVerified email at math.unipd.it
Nicola ZannoneEindhoven University of TechnologyVerified email at tue.nl
Laura GengaEindhoven University of TechnlogyVerified email at tue.nl
Felix MannhardtSINTEF Digital, Technology ManagementVerified email at sintef.no
Bart HompesEindhoven University of TechnologyVerified email at tue.nl
Prabhakar DixitPhD StudentVerified email at tue.nl
Dan IonitaUniversity of TwenteVerified email at utwente.nl

Niek Tax

Eindhoven University of Technology

Verified email at tue.nl - Homepage

Machine Learning Sequence Models Data Mining Pattern Mining Process Mining


Title	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	96	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	52	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	46	2015
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	37	2016
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	23	2016
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	22	2018
Predicting The Dutch Football Competition Using Public Data: A Machine Learning Approach N Tax, Y Joustra 2014, 2014	18	2014
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	12	2017
Unsupervised Event Abstraction using Pattern Abstraction and Local Process Models F Mannhardt, N Tax International Working Conference on Business Process Modeling, Development …, 2017	12	2017
On generation of time-based label refinements N Tax, E Alasgarov, N Sidorova, R Haakma Proceedings of the 25th International Workshop on Concurrency, Specification …, 2016	11	2016
Log-based evaluation of label splits for process models N Tax, N Sidorova, R Haakma, WMP van der Aalst Procedia Computer Science 96, 63-72, 2016	9	2016
On the Use of Hierarchical Subtrace Mining for Efficient Local Process Model Mining N Tax, L Genga, N Zannone Proceedings of the International Symposium on Data-driven Process Discovery …, 2017	6	2017
Heuristics for High-Utility Local Process Model Mining B Dalmas, N Tax, S Norre Proceedings of the International Workshop on Algorithms & Theories for the …, 2017	6	2017
Interest-Driven Discovery of Local Process Models N Tax, B Dalmas, N Sidorova, WMP van der Aalst, S Norre Information Systems, 2018	5	2018
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	4	2017
An interdisciplinary comparison of sequence modeling methods for next-element prediction N Tax, I Teinemaa, SJ van Zelst arXiv preprint arXiv:1811.00062, 2018	3	2018
Alarm-based prescriptive process monitoring I Teinemaa, N Tax, M de Leoni, M Dumas, FM Maggi International Conference on Business Process Management, 91-107, 2018	3	2018
LocalProcessModelDiscovery: Bringing Petri Nets to the Pattern Mining World N Tax, N Sidorova, WMP van der Aalst, R Haakma Application and Theory of Petri Nets and Concurrency, 2018	3	2018
Scaling Learning to Rank to Big Data N Tax, D Hiemstra, SB Trieschnigg, Dolf	3*	2014
Scaling Learning to Rank to Big Data: Using MapReduce to Parallelise Learning to Rank N Tax University of Twente, 2014	3	2014

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