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Arik Senderovich
Tytuł
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Queue mining for delay prediction in multi-class service processes
A Senderovich, M Weidlich, A Gal, A Mandelbaum
Information systems 53, 278-295, 2015
1432015
Queue mining–predicting delays in service processes
A Senderovich, M Weidlich, A Gal, A Mandelbaum
Advanced Information Systems Engineering: 26th International Conference …, 2014
1412014
Intra and inter-case features in predictive process monitoring: A tale of two dimensions
A Senderovich, C Di Francescomarino, C Ghidini, K Jorbina, FM Maggi
Business Process Management: 15th International Conference, BPM 2017 …, 2017
1402017
Traveling time prediction in scheduled transportation with journey segments
A Gal, A Mandelbaum, F Schnitzler, A Senderovich, M Weidlich
Information Systems 64, 266-280, 2017
1382017
The ROAD from sensor data to process instances via interaction mining
A Senderovich, A Rogge-Solti, A Gal, J Mendling, A Mandelbaum
Advanced Information Systems Engineering: 28th International Conference …, 2016
712016
Conformance checking and performance improvement in scheduled processes: A queueing-network perspective
A Senderovich, M Weidlich, L Yedidsion, A Gal, A Mandelbaum, S Kadish, ...
Information Systems 62, 185-206, 2016
672016
From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring
A Senderovich, C Di Francescomarino, FM Maggi
Information Systems 84, 255-264, 2019
532019
In log and model we trust? A generalized conformance checking framework
A Rogge-Solti, A Senderovich, M Weidlich, J Mendling, A Gal
Business Process Management: 14th International Conference, BPM 2016, Rio de …, 2016
482016
Discovering queues from event logs with varying levels of information
A Senderovich, SJJ Leemans, S Harel, A Gal, A Mandelbaum, ...
Business Process Management Workshops: BPM 2015, 13th International …, 2016
442016
How much event data is enough? A statistical framework for process discovery
M Bauer, A Senderovich, A Gal, L Grunske, M Weidlich
Advanced Information Systems Engineering: 30th International Conference …, 2018
422018
Generating complex, realistic cloud workloads using recurrent neural networks
S Bergsma, T Zeyl, A Senderovich, JC Beck
Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles …, 2021
342021
To aggregate or to eliminate? Optimal model simplification for improved process performance prediction
A Senderovich, A Shleyfman, M Weidlich, A Gal, A Mandelbaum
Information Systems 78, 96-111, 2018
312018
Data-driven performance analysis of scheduled processes
A Senderovich, A Rogge-Solti, A Gal, J Mendling, A Mandelbaum, ...
Business Process Management: 13th International Conference, BPM 2015 …, 2015
302015
Mining resource scheduling protocols
A Senderovich, M Weidlich, A Gal, A Mandelbaum
Business Process Management: 12th International Conference, BPM 2014, Haifa …, 2014
282014
Congestion graphs for automated time predictions
A Senderovich, JC Beck, A Gal, M Weidlich
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4854-4861, 2019
272019
Can I trust my simulation model? measuring the quality of business process simulation models
D Chapela-Campa, I Benchekroun, O Baron, M Dumas, D Krass, ...
International Conference on Business Process Management, 20-37, 2023
222023
An Ising framework for constrained clustering on special purpose hardware
E Cohen, A Senderovich, JC Beck
Integration of Constraint Programming, Artificial Intelligence, and …, 2020
212020
Temporal network representation of event logs for improved performance modelling in business processes
A Senderovich, M Weidlich, A Gal
Business Process Management: 15th International Conference, BPM 2017 …, 2017
192017
P-folder: optimal model simplification for improving accuracy in process performance prediction
A Senderovich, A Shleyfman, M Weidlich, A Gal, A Mandelbaum
International Conference on Business Process Management, 418-436, 2016
182016
Context-aware temporal network representation of event logs: Model and methods for process performance analysis
A Senderovich, M Weidlich, A Gal
Information Systems 84, 240-254, 2019
162019
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