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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:

Deep Probabilistic Matrix Factorization Framework for Online Collaborative Filtering
Kangkang Li, Xiuze Zhou, Fan Lin, et al.
IEEE Access (2019) Vol. 7, pp. 56117-56128
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Online learning: A comprehensive survey
Steven C. H. Hoi, Doyen Sahoo, Jing Lu, et al.
Neurocomputing (2021) Vol. 459, pp. 249-289
Open Access | Times Cited: 376
Deep Learning Architecture for Collaborative Filtering Recommender Systems
Jesús Bobadilla, Santiago Alonso, Antonio Hernando
Applied Sciences (2020) Vol. 10, Iss. 7, pp. 2441-2441
Open Access | Times Cited: 97
Classification-based Deep Neural Network Architecture for Collaborative Filtering Recommender Systems
Jesús Bobadilla, Fernando Ortega, Abraham Gutiérrez, et al.
International Journal of Interactive Multimedia and Artificial Intelligence (2020) Vol. 6, Iss. 1, pp. 68-68
Open Access | Times Cited: 56
A deep neural network-based collaborative filtering using a matrix factorization with a twofold regularization
Armielle Noulapeu Ngaffo, Zièd Choukair
Neural Computing and Applications (2022) Vol. 34, Iss. 9, pp. 6991-7003
Closed Access | Times Cited: 23
In-depth survey: deep learning in recommender systems—exploring prediction and ranking models, datasets, feature analysis, and emerging trends
Shivangi Gheewala, Shuxiang Xu, Soonja Yeom
Neural Computing and Applications (2025)
Open Access
DeepRank: Learning to rank with neural networks for recommendation
Ming Chen, Xiuze Zhou
Knowledge-Based Systems (2020) Vol. 209, pp. 106478-106478
Closed Access | Times Cited: 36
Multi-criteria recommender system based on social relationships and criteria preferences
Kun Zhang, Xinwang Liu, Weizhong Wang, et al.
Expert Systems with Applications (2021) Vol. 176, pp. 114868-114868
Closed Access | Times Cited: 28
Enhanced fractional prediction scheme for effective matrix factorization in chaotic feedback recommender systems
Zeshan Aslam Khan, Naveed Ishtiaq Chaudhary, Taimoor Ali Khan, et al.
Chaos Solitons & Fractals (2023) Vol. 176, pp. 114109-114109
Closed Access | Times Cited: 11
Graph-Based Feature Crossing to Enhance Recommender Systems
Congyu Cai, Hong Chen, Yang Liu, et al.
Mathematics (2025) Vol. 13, Iss. 2, pp. 302-302
Open Access
Design of Momentum Fractional Stochastic Gradient Descent for Recommender Systems
Zeshan Aslam Khan, Syed Zubair, Hani Alquhayz, et al.
IEEE Access (2019) Vol. 7, pp. 179575-179590
Open Access | Times Cited: 28
Design of normalized fractional SGD computing paradigm for recommender systems
Zeshan Aslam Khan, Syed Zubair, Naveed Ishtiaq Chaudhary, et al.
Neural Computing and Applications (2019) Vol. 32, Iss. 14, pp. 10245-10262
Closed Access | Times Cited: 27
Collaborative Deep Forest Learning for Recommender Systems
Soheila Molaei, Amirhossein Havvaei, Hadi Zare, et al.
IEEE Access (2021) Vol. 9, pp. 22053-22061
Open Access | Times Cited: 20
Increasing the Effectiveness of Prediction in Recommendation Engines Based on Collaborative Filtering
Roaa Faleh Mahdi
Bilad Alrafidain Journal for Engineering Science and Technology (2024) Vol. 3, Iss. 1, pp. 47-58
Open Access | Times Cited: 2
Matrix Factorization in Recommender Systems: Algorithms, Applications, and Peculiar Challenges
Folasade Olubusola Isinkaye
IETE Journal of Research (2021) Vol. 69, Iss. 9, pp. 6087-6100
Closed Access | Times Cited: 16
Rating prediction of recommended item based on review deep learning and rating probability matrix factorization
Zhiguo Zhu, Mengru Yan, Xiaoyi Deng, et al.
Electronic Commerce Research and Applications (2022) Vol. 54, pp. 101160-101160
Closed Access | Times Cited: 12
A Bayesian Inference Based Hybrid Recommender System
Armielle Noulapeu Ngaffo, Walid El Ayeb, Zièd Choukair
IEEE Access (2020) Vol. 8, pp. 101682-101701
Open Access | Times Cited: 13
A Collaborative Filtering Probabilistic Approach for Recommendation to Large Homogeneous and Automatically Detected Groups
Jesús Bobadilla, Abraham Gutiérrez, Santiago Alonso, et al.
International Journal of Interactive Multimedia and Artificial Intelligence (2020) Vol. 6, Iss. 2, pp. 11-11
Open Access | Times Cited: 12
IUAutoTimeSVD++: A Hybrid Temporal Recommender System Integrating Item and User Features Using a Contractive Autoencoder
Abdelghani Azri, Adil Haddi, Hakim Allali
Information (2024) Vol. 15, Iss. 4, pp. 204-204
Open Access | Times Cited: 1
MISGD: Moving-Information-Based Stochastic Gradient Descent Paradigm for Personalized Fuzzy Recommender Systems
Zeshan Aslam Khan, Muhammad Asif Zahoor Raja, Naveed Ishtiaq Chaudhary, et al.
International Journal of Fuzzy Systems (2021) Vol. 24, Iss. 1, pp. 686-712
Closed Access | Times Cited: 10
NeuRank: learning to rank with neural networks for drug–target interaction prediction
Xiujin Wu, Wenhua Zeng, Fan Lin, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 10
A Survey of One Class E-Commerce Recommendation System Techniques
Mohamed Khoali, Yassin Laaziz, Abdelhak Tali, et al.
Electronics (2022) Vol. 11, Iss. 6, pp. 878-878
Open Access | Times Cited: 7
Enhancing the scalability of distance-based link prediction algorithms in recommender systems through similarity selection
Zhan Su, Zhong Huang, Jun Ai, et al.
PLoS ONE (2022) Vol. 17, Iss. 7, pp. e0271891-e0271891
Open Access | Times Cited: 6
An Intelligent Platform for Offline Learners Based on Model-Driven Crowdsensing Over Intermittent Networks
Shin’ichi Konomi, Lulu Gao, Doreen Mushi
Lecture notes in computer science (2020), pp. 300-314
Closed Access | Times Cited: 8
Social network-based News Recommendation with Knowledge Graph
Jing Yang, Jing Wan, Yunxiang Wang, et al.
(2020), pp. 1255-1260
Closed Access | Times Cited: 6
Efficient Distributed Matrix Factorization Alternating Least Squares (EDMFALS) for Recommendation Systems Using Spark
Rahul Kumar, G. Appa Rao, S. Anuradha
Journal of Information & Knowledge Management (2021) Vol. 21, Iss. 01
Closed Access | Times Cited: 6
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