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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:

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: 14

Showing 14 citing articles:

Graph neural networks for financial fraud detection: a review
Dawei Cheng, Yao Zou, Sheng Xiang, et al.
Frontiers of Computer Science (2025) Vol. 19, Iss. 9
Open Access | Times Cited: 1
Federated Semantic Web Framework for Enhanced Financial Risk Control and Data Analysis
Siwei Wang
International Journal on Semantic Web and Information Systems (2025) Vol. 21, Iss. 1, pp. 1-19
Open Access
Expanding and Interpreting Financial Statement Fraud Detection Using Supply Chain Knowledge Graphs
Shanshan Zhu, Ting Ma, Haotian Wu, et al.
Journal of theoretical and applied electronic commerce research (2025) Vol. 20, Iss. 1, pp. 26-26
Open Access
A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models
Ziqi Yuan, Qingyun Sun, Haoyi Zhou, et al.
International Journal of Machine Learning and Cybernetics (2025)
Closed Access
Transaction fraud detection via attentional spatial–temporal GNN
Samiyeh Khosravi, Mehrdad Kargari, Babak Teimourpour, et al.
The Journal of Supercomputing (2025) Vol. 81, Iss. 4
Closed Access
Fraud detection in multi-relation graph: Contrastive Learning on Feature and Structural Levels
Jiangnan Tang, Huanhuan Gu, Darko Vuković, et al.
Neurocomputing (2025), pp. 130063-130063
Closed Access
Anomaly Detection in Dynamic Graphs: A Comprehensive Survey
Ocheme Anthony Ekle, William Eberle
ACM Transactions on Knowledge Discovery from Data (2024) Vol. 18, Iss. 8, pp. 1-44
Open Access | Times Cited: 3
An imbalanced learning method based on graph tran-smote for fraud detection
Jintao Wen, Xianghong Tang, Jianguang Lu
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Spatio-temporal graph attention network-based detection of FDIA from smart meter data at geographically hierarchical levels
Md Abul Hasnat, Harsh Anand, Mazdak Tootkaboni, et al.
Electric Power Systems Research (2024) Vol. 238, pp. 111149-111149
Closed Access | Times Cited: 1
Artificial Intelligence Techniques for Fraud Detection
Guangsheng Lai
(2023)
Open Access | Times Cited: 3
Fraud Detection Based on Credit Review Texts with Dual Channel Memory Networks
Yansong Wang, Defu Lian, Enhong Chen
Applied Artificial Intelligence (2024) Vol. 38, Iss. 1
Open Access
Beyond Homophily: Neighborhood Distribution-guided Graph Convolutional Networks
Siqi Liu, Dongxiao He, Zhizhi Yu, et al.
Expert Systems with Applications (2024) Vol. 259, pp. 125274-125274
Closed Access
Graph neural network for fraud detection via context encoding and adaptive aggregation
Chaoli Lou, Yueyang Wang, Jianing Li, et al.
Expert Systems with Applications (2024), pp. 125473-125473
Closed Access
GemmaWithLoRA: A New Approach to Click Fraud Detection
Bin Dai, Lei Wang, Xiaoyan Zhao, et al.
(2024), pp. 1-8
Closed Access
Scenic spot path planning and journey customization based on multilayer hybrid hypernetwork optimization
Chunqiao Song
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0308135-e0308135
Open Access
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