OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Prediction-based Resource Allocation using LSTM and Minimum Cost and Maximum Flow Algorithm
Gyunam Park, Minseok Song
(2019), pp. 121-128
Closed Access | Times Cited: 43
Gyunam Park, Minseok Song
(2019), pp. 121-128
Closed Access | Times Cited: 43
Showing 1-25 of 43 citing articles:
Explainable Predictive Process Monitoring
Riccardo Galanti, Bernat Coma-Puig, Massimiliano de Leoni, et al.
(2020)
Open Access | Times Cited: 51
Riccardo Galanti, Bernat Coma-Puig, Massimiliano de Leoni, et al.
(2020)
Open Access | Times Cited: 51
A Multi-View Deep Learning Approach for Predictive Business Process Monitoring
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, et al.
IEEE Transactions on Services Computing (2021) Vol. 15, Iss. 4, pp. 2382-2395
Closed Access | Times Cited: 43
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, et al.
IEEE Transactions on Services Computing (2021) Vol. 15, Iss. 4, pp. 2382-2395
Closed Access | Times Cited: 43
An explainable decision support system for predictive process analytics
Riccardo Galanti, Massimiliano de Leoni, Merylin Monaro, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105904-105904
Open Access | Times Cited: 21
Riccardo Galanti, Massimiliano de Leoni, Merylin Monaro, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105904-105904
Open Access | Times Cited: 21
The Business Process Optimization Competition
Felix Schumann, Matthias Ehrendorfer, Michel Kunkler, et al.
Lecture notes in business information processing (2025), pp. 61-72
Closed Access
Felix Schumann, Matthias Ehrendorfer, Michel Kunkler, et al.
Lecture notes in business information processing (2025), pp. 61-72
Closed Access
Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event prediction with deep learning
Kai Heinrich, Patrick Zschech, Christian Janiesch, et al.
Decision Support Systems (2021) Vol. 143, pp. 113494-113494
Open Access | Times Cited: 36
Kai Heinrich, Patrick Zschech, Christian Janiesch, et al.
Decision Support Systems (2021) Vol. 143, pp. 113494-113494
Open Access | Times Cited: 36
Triggering Proactive Business Process Adaptations via Online Reinforcement Learning
Andreas Metzger, Tristan Kley, Alexander Palm
Lecture notes in computer science (2020), pp. 273-290
Closed Access | Times Cited: 36
Andreas Metzger, Tristan Kley, Alexander Palm
Lecture notes in computer science (2020), pp. 273-290
Closed Access | Times Cited: 36
Modelling Data-Aware Stochastic Processes - Discovery and Conformance Checking
Felix Mannhardt, Sander J. J. Leemans, Christopher T. Schwanen, et al.
Lecture notes in computer science (2023), pp. 77-98
Closed Access | Times Cited: 11
Felix Mannhardt, Sander J. J. Leemans, Christopher T. Schwanen, et al.
Lecture notes in computer science (2023), pp. 77-98
Closed Access | Times Cited: 11
Performance-preserving event log sampling for predictive monitoring
Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, et al.
Journal of Intelligent Information Systems (2023) Vol. 61, Iss. 1, pp. 53-82
Open Access | Times Cited: 8
Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park, et al.
Journal of Intelligent Information Systems (2023) Vol. 61, Iss. 1, pp. 53-82
Open Access | Times Cited: 8
Deep Reinforcement Learning for Resource Allocation in Business Processes
Kamil Żbikowski, Michał Ostapowicz, Piotr Gawrysiak
Lecture notes in business information processing (2023), pp. 177-189
Open Access | Times Cited: 7
Kamil Żbikowski, Michał Ostapowicz, Piotr Gawrysiak
Lecture notes in business information processing (2023), pp. 177-189
Open Access | Times Cited: 7
Optimizing Resource Allocation Based on Predictive Process Monitoring
Gyunam Park, Minseok Song
IEEE Access (2023) Vol. 11, pp. 38309-38323
Open Access | Times Cited: 5
Gyunam Park, Minseok Song
IEEE Access (2023) Vol. 11, pp. 38309-38323
Open Access | Times Cited: 5
A fault-tolerant hybrid resource allocation model for dynamic computational grid
Sophiya Sheikh, A. Nagaraju, Mohammad Shahid
Journal of Computational Science (2020) Vol. 48, pp. 101268-101268
Closed Access | Times Cited: 14
Sophiya Sheikh, A. Nagaraju, Mohammad Shahid
Journal of Computational Science (2020) Vol. 48, pp. 101268-101268
Closed Access | Times Cited: 14
Automatically reconciling the trade-off between prediction accuracy and earliness in prescriptive business process monitoring
Andreas Metzger, Tristan Kley, Aristide Rothweiler, et al.
Information Systems (2023) Vol. 118, pp. 102254-102254
Open Access | Times Cited: 5
Andreas Metzger, Tristan Kley, Aristide Rothweiler, et al.
Information Systems (2023) Vol. 118, pp. 102254-102254
Open Access | Times Cited: 5
Learning to Act: A Reinforcement Learning Approach to Recommend the Best Next Activities
Stefano Branchi, Chiara Di Francescomarino, Chiara Ghidini, et al.
Lecture notes in business information processing (2022), pp. 137-154
Closed Access | Times Cited: 8
Stefano Branchi, Chiara Di Francescomarino, Chiara Ghidini, et al.
Lecture notes in business information processing (2022), pp. 137-154
Closed Access | Times Cited: 8
Optimizing Resource Allocation Policies in Real-World Business Processes Using Hybrid Process Simulation and Deep Reinforcement Learning
Francesca Meneghello, Jeroen Middelhuis, Laura Genga, et al.
Lecture notes in computer science (2024), pp. 167-184
Closed Access | Times Cited: 1
Francesca Meneghello, Jeroen Middelhuis, Laura Genga, et al.
Lecture notes in computer science (2024), pp. 167-184
Closed Access | Times Cited: 1
Explainable Process Prescriptive Analytics
Alessandro Padella, Massimiliano de Leoni, Onur Doğan, et al.
(2022), pp. 16-23
Closed Access | Times Cited: 7
Alessandro Padella, Massimiliano de Leoni, Onur Doğan, et al.
(2022), pp. 16-23
Closed Access | Times Cited: 7
Design and Evaluation of a User Interface Concept for Prescriptive Process Monitoring
Kateryna Kubrak, Fredrik Milani, Alexander Nolte, et al.
Lecture notes in computer science (2023), pp. 347-363
Open Access | Times Cited: 3
Kateryna Kubrak, Fredrik Milani, Alexander Nolte, et al.
Lecture notes in computer science (2023), pp. 347-363
Open Access | Times Cited: 3
Step-by-Step Case ID Identification Based on Activity Connection for Cross-Organizational Process Mining
K Tajima, Bojian Du, Yoshiaki Narusue, et al.
IEEE Access (2023) Vol. 11, pp. 60578-60589
Open Access | Times Cited: 3
K Tajima, Bojian Du, Yoshiaki Narusue, et al.
IEEE Access (2023) Vol. 11, pp. 60578-60589
Open Access | Times Cited: 3
Process-Aware Enterprise Social Network Prediction and Experiment Using LSTM Neural Network Models
Dinh-Lam Pham, Hyun Ahn, Kyoung-Sook Kim, et al.
IEEE Access (2021) Vol. 9, pp. 57922-57940
Open Access | Times Cited: 7
Dinh-Lam Pham, Hyun Ahn, Kyoung-Sook Kim, et al.
IEEE Access (2021) Vol. 9, pp. 57922-57940
Open Access | Times Cited: 7
A survey on recommendation in process mining
Mansoureh Yari Eili, Jalal Rezaeenour
Concurrency and Computation Practice and Experience (2022) Vol. 34, Iss. 26
Open Access | Times Cited: 4
Mansoureh Yari Eili, Jalal Rezaeenour
Concurrency and Computation Practice and Experience (2022) Vol. 34, Iss. 26
Open Access | Times Cited: 4
Workforce Upskilling: A History-Based Approach for Recommending Unfamiliar Process Activities
Anastasiia Pika, Moe Thandar Wynn
Lecture notes in computer science (2020), pp. 334-349
Open Access | Times Cited: 4
Anastasiia Pika, Moe Thandar Wynn
Lecture notes in computer science (2020), pp. 334-349
Open Access | Times Cited: 4
Deep Learning-based LAP Deployment and Aerial Infrastructure Sharing in 6G
Tushar Vrind, Sudharshan Rao, Lalit Pathak, et al.
2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) (2020), pp. 1-5
Closed Access | Times Cited: 4
Tushar Vrind, Sudharshan Rao, Lalit Pathak, et al.
2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) (2020), pp. 1-5
Closed Access | Times Cited: 4
Predictive Analytics for Object-Centric Processes: Do Graph Neural Networks Really Help?
Riccardo Galanti, Massimiliano de Leoni
Lecture notes in business information processing (2024), pp. 521-533
Closed Access
Riccardo Galanti, Massimiliano de Leoni
Lecture notes in business information processing (2024), pp. 521-533
Closed Access
Optimizing Costs for Cloud-Based Long-Running Activities using ILP
Riane Driss, Ettazi Widad, Ahmed Ettalbi
(2024), pp. 1-6
Closed Access
Riane Driss, Ettazi Widad, Ahmed Ettalbi
(2024), pp. 1-6
Closed Access
A Universal Approach to Feature Representation in Dynamic Task Assignment Problems
Riccardo Lo Bianco, Remco Dijkman, Wim Nuijten, et al.
Lecture notes in business information processing (2024), pp. 197-213
Closed Access
Riccardo Lo Bianco, Remco Dijkman, Wim Nuijten, et al.
Lecture notes in business information processing (2024), pp. 197-213
Closed Access
Online Resource Allocation to Process Tasks Under Uncertain Resource Availabilities
Michel Kunkler, Stefanie Rinderle‐Ma
(2024), pp. 137-144
Closed Access
Michel Kunkler, Stefanie Rinderle‐Ma
(2024), pp. 137-144
Closed Access
