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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:

Improving fraud detection via hierarchical attention-based Graph Neural Network
Yajing Liu, Zhengya Sun, Wensheng Zhang
Journal of Information Security and Applications (2022) Vol. 72, pp. 103399-103399
Open Access | Times Cited: 20

Showing 20 citing articles:

Medicare Fraud Detection Using Graph Analysis: A Comparative Study of Machine Learning and Graph Neural Networks
Yeeun Yoo, Jin-Ho Shin, S.-H. Kyeong
IEEE Access (2023) Vol. 11, pp. 88278-88294
Open Access | Times Cited: 21
Fraud detection on multi-relation graphs via imbalanced and interactive learning
Xiaodi Wang, Zhonglin Liu, Jiamiao Liu, et al.
Information Sciences (2023) Vol. 642, pp. 119153-119153
Closed Access | Times Cited: 15
SCN_GNN: A GNN-based fraud detection algorithm combining strong node and graph topology information
Jing Chen, Quanzhen Chen, Feng Jiang, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121643-121643
Closed Access | Times Cited: 15
Graph anomaly detection based on hybrid node representation learning
Xiang Wang, Hao Dou, Dibo Dong, et al.
Neural Networks (2025) Vol. 185, pp. 107169-107169
Closed Access
Real‐Time Monitoring of On‐Board Unit Status in Highway Electronic Toll Collection Systems Using Graphsage‐Based Heterogeneous Graph Learning
Qiang Ren, Changfeng Yan, Fumin Zou, et al.
Concurrency and Computation Practice and Experience (2025) Vol. 37, Iss. 6-8
Closed Access
Graph-Based Syntactic Analysis for Cross-Domain Fraud Messages Detection
Ning-Fang Hsu, Yi-Shin Chen
Communications in computer and information science (2025), pp. 33-48
Closed Access
Financial transaction fraud detector based on imbalance learning and graph neural network
Guoxiang Tong, Jieyu Shen
Applied Soft Computing (2023) Vol. 149, pp. 110984-110984
Closed Access | Times Cited: 7
Two-stage GNN-based fraud detection with camouflage identification and enhanced semantics aggregation
Jun Zhang, Jianguang Lu, Xianghong Tang
Neurocomputing (2023) Vol. 570, pp. 127108-127108
Closed Access | Times Cited: 7
A new machine learning model for predicting the water quality index
Elham Ghanbari-Adivi
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 4, pp. 5635-5667
Closed Access | Times Cited: 2
Enhancing Fraud Detection in Banking with Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention
Fawaz Khaled Alarfaj, Shabnam Shahzadi
IEEE Access (2024) Vol. 13, pp. 20633-20646
Open Access | Times Cited: 2
Medicare fraud detection using graph neural networks
Yeeun Yoo, Dong-Hwa Shin, Dae‐Hee Han, et al.
2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (2022), pp. 1-5
Closed Access | Times Cited: 4
Transformer-Based Language Deep Learning Detection of Fake Reviews on Online Products
Maysara Mazin Badr Alsaad
Deleted Journal (2024) Vol. 20, Iss. 3, pp. 2368-2378
Open Access
A Survey on Graph Neural Networks for Fraud Detection in Ride Hailing Platforms
Kanishka Hewageegana, Janani Harischandra, Nipuna Senanayake, et al.
(2024), pp. 168-179
Closed Access
Fake review detection with label-consistent and hierarchical-relation-aware graph contrastive learning
Jianrong Yao, Ling Jiang, Chenglong Shi, et al.
Knowledge-Based Systems (2024) Vol. 302, pp. 112385-112385
Closed Access
BalancerGNN: Balancer Graph Neural Networks for imbalanced datasets: A case study on fraud detection
Mallika Boyapati, Ramazan Aygün
Neural Networks (2024) Vol. 182, pp. 106926-106926
Closed Access
Research on Fraud Detection Method Based on Heterogeneous Graph Representation Learning
Xuxu Zheng, Feng Chen, Zhiyi Yin, et al.
Electronics (2023) Vol. 12, Iss. 14, pp. 3070-3070
Open Access | Times Cited: 1
Detection of E-Commerce Fraud Review via Self-Paced Graph Contrast Learning
Weidong Zhao, Xiaotong Liu
The Computer Journal (2023) Vol. 67, Iss. 6, pp. 2054-2065
Closed Access | Times Cited: 1
A Fraud Detection System in Financial Networks Using AntiBenford Subgraphs and Machine Learning Algorithms
Rachna Somkunwar, Amit Pimpalkar, Kartik M. Katakdound, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 1
HITS-GNN: A Simplified Propagation Scheme for Graph Neural Networks
Mehak Khan, Gustavo Borges Moreno e Mello, Paal Engelstad, et al.
2021 IEEE International Conference on Big Data (Big Data) (2022), pp. 5514-5519
Closed Access | Times Cited: 2
Flower Pollination Optimization Algorithm with Stacked Temporal Convolution Network based Classification for financial anomaly Fraud Detection
N. Krishnavardhan, M. Govindarajan, Achutha Rao S.V
Research Square (Research Square) (2023)
Open Access
Fake Review Detection with Hierarchical Lable&Relation-Aware Graph Contrastive Learning
Jianrong Yao, Ling Jiang, Chenglong Shi, et al.
(2023)
Closed Access
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