| 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 | 649 | 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 | 156 | 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 | 134 | 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 | 123 | 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 | 114 | 2017 |
| Predicting The Dutch Football Competition Using Public Data: A Machine Learning Approach N Tax, Y Joustra Transactions of Knowledge and Data Engineering (TKDE), 2014 | 97 | 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 | 92 | 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 | 71 | 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 | 68 | 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 | 68 | 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 | 62 | 2021 |
| Human Activity Prediction in Smart Home Environments with LSTM Neural Networks N Tax Proceedings of the International Conference on Intelligent Environments, 2018 | 60 | 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 | 47 | 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 |
| 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 | 26 | 2023 |
| 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 | 26* | 2019 |
| Interest-Driven Discovery of Local Process Models N Tax, B Dalmas, N Sidorova, WMP van der Aalst, S Norre Information Systems, 2018 | 25 | 2018 |
| 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 | 22 | 2021 |
| Causal reasoning over control-flow decisions in process models SJJ Leemans, N Tax International Conference on Advanced Information Systems Engineering, 183-200, 2022 | 20 | 2022 |
Wil van der AalstProfessor of Process and Data Science, RWTH Aachen University || Celonis || Fraunhofer FIT || TU/e確認したメール アドレス: pads.rwth-aachen.de