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OpenAlex Citation Counts

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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:

Predictive Process Monitoring
Chiara Di Francescomarino, Chiara Ghidini
Lecture notes in business information processing (2022), pp. 320-346
Open Access | Times Cited: 59

Showing 26-50 of 59 citing articles:

Demystifying Data Governance for Process Mining: Insights from a Delphi Study
Kanika Goel, Niels Martin, Arthur H. M. ter Hofstede
Information & Management (2024) Vol. 61, Iss. 5, pp. 103973-103973
Open Access | Times Cited: 1
Model-Based Recommendations for Next-Best Actions in Knowledge-Intensive Processes
Anjo Seidel, Stephan Haarmann, Mathias Weske
Lecture notes in computer science (2024), pp. 195-211
Closed Access | Times Cited: 1
Attention Please: What Transformer Models Really Learn for Process Prediction
Martin Käppel, Lars Ackermann, Stefan Jablonski, et al.
Lecture notes in computer science (2024), pp. 203-220
Closed Access | Times Cited: 1
Predictive process monitoring: concepts, challenges, and future research directions
Paolo Ceravolo, Marco Comuzzi, Jochen De Weerdt, et al.
Deleted Journal (2024) Vol. 1, Iss. 1
Open Access | Times Cited: 1
Structural positional encoding for knowledge integration in transformer-based medical process monitoring and trace classification
Christopher Irwin, Marco Dossena, Giorgio Leonardi, et al.
Progress in Artificial Intelligence (2024)
Closed Access | Times Cited: 1
Using Process Mining in Healthcare
Niels Martin, Nils Wittig, Jorge Muñoz-Gama
Lecture notes in business information processing (2022), pp. 416-444
Open Access | Times Cited: 5
Responsible Process Mining
Felix Mannhardt
Lecture notes in business information processing (2022), pp. 373-401
Open Access | Times Cited: 4
When to Invoke a Prediction Service for Business Process Monitoring?
Jian Cao, Naixuan Wang, Shiyou Qian, et al.
IEEE Transactions on Services Computing (2023) Vol. 16, Iss. 4, pp. 3061-3074
Closed Access | Times Cited: 2
Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction
Jorg W. R. Bekelaar, Jolanda J. Luime, Renata Medeiros de Carvalho
Lecture notes in business information processing (2023), pp. 378-390
Open Access | Times Cited: 2
Formulating the potentials of clustering of event data over multiple entities for decision support: a network embeddings approach
Pavlos Delias, Daniela Grigori
Journal of Decision System (2023) Vol. 33, Iss. 4, pp. 721-743
Closed Access | Times Cited: 2
Predictive Process Monitoring for Prediction of Remaining Cycle Time in Automated Manufacturing: A Case Study
Jonas Friederich, Jonas Kristoffer Lindeløv, Sanja Lazarova‐Molnar
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) (2023), pp. 1-8
Open Access | Times Cited: 2
TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments
Vincenzo Pasquadibisceglie, Annalisa Appice, Giuseppe Ieva, et al.
Journal of Intelligent Information Systems (2023) Vol. 62, Iss. 3, pp. 705-733
Closed Access | Times Cited: 2
Business process remaining time prediction using explainable reachability graph from gated RNNs
Rui Cao, Qingtian Zeng, Weijian Ni, et al.
Applied Intelligence (2022) Vol. 53, Iss. 11, pp. 13178-13191
Closed Access | Times Cited: 3
Simulating Cyber-Attack Scenarios by Discovering Petri-Nets from Large-Scale Event Logs
M. Makwana, Vedant Thakkar, Debanshu Das, et al.
(2024), pp. 49-54
Closed Access
Empirical Insights into Context-Aware Process Predictions: Model Selection and Context Integration
Marc C. Hennig
Lecture notes in business information processing (2024), pp. 323-334
Closed Access
Accelerating real-time deterministic discovery through single instruction multiple data graphical processor unit for executing distributed event logs
Hermawan Bin Fauzan, Riyanarto Sarno, Ahmad Saikhu
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2024) Vol. 14, Iss. 4, pp. 4214-4214
Open Access
Integrating Predictive Process Monitoring Techniques in Smart Agriculture
Simona Fioretto, Dino Ienco, Roberto Interdonato, et al.
Lecture notes in computer science (2024), pp. 306-313
Open Access
Exploiting recurrent graph neural networks for suffix prediction in predictive monitoring
Efrén Rama-Maneiro, Juan C. Vidal, Manuel Lama, et al.
Computing (2024) Vol. 106, Iss. 9, pp. 3085-3111
Closed Access
Supporting Interpretability in Predictive Process Monitoring Using Process Maps
Ana Rocío Cárdenas Maita, Marcelo Fantinato, Sarajane Marques Peres, et al.
Lecture notes in business information processing (2024), pp. 230-246
Closed Access
Towards discovering erratic behavior in robotic process automation with statistical process control
Petr Průcha
Information Systems and e-Business Management (2024)
Open Access
Efficient Training of Recurrent Neural Networks for Remaining Time Prediction in Predictive Process Monitoring
Johannes Roider, Dario Zanca, Bjoern M. Eskofier
Lecture notes in computer science (2024), pp. 238-255
Closed Access
A Conceptual Framework for Predictive Process Monitoring in Public Administration
Simona Fioretto, Elio Masciari
Lecture notes on data engineering and communications technologies (2024), pp. 423-431
Closed Access
Nirdizati: an advanced predictive process monitoring toolkit
Williams Rizzi, Chiara Di Francescomarino, Chiara Ghidini, et al.
Journal of Intelligent Information Systems (2024)
Open Access
Enhancing Predictive Process Monitoring with Sequential Graphs and Trace Attention
Yi Deng, Jian Wang, Chong Wang, et al.
(2024), pp. 406-415
Closed Access
Predicting schedule adherence of engineering changes – a case study on effectivity date adherence prediction using machine learning
Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg, et al.
International Journal of Production Research (2024), pp. 1-25
Open Access

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