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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:

Credit Card Fraud Detection: A Novel Approach Using Aggregation Strategy and Feedback Mechanism
Changjun Jiang, Jiahui Song, Guanjun Liu, et al.
IEEE Internet of Things Journal (2018) Vol. 5, Iss. 5, pp. 3637-3647
Closed Access | Times Cited: 148

Showing 1-25 of 148 citing articles:

Credit Card Fraud Detection using Machine Learning Algorithms
Vaishnavi Nath Dornadula, S. Geetha
Procedia Computer Science (2019) Vol. 165, pp. 631-641
Open Access | Times Cited: 249
A Privacy-Aware and Incremental Defense Method Against GAN-Based Poisoning Attack
Feifei Qiao, Zhong Li, Yubo Kong
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 2, pp. 1708-1721
Closed Access | Times Cited: 214
Credit card fraud detection using artificial neural network
Asha RB, Suresh Kumar KR
Global Transitions Proceedings (2021) Vol. 2, Iss. 1, pp. 35-41
Open Access | Times Cited: 205
Machine learning techniques for credit risk evaluation: a systematic literature review
Siddharth Bhatore, Lalit Mohan, Y. Raghu Reddy
Journal of Banking and Financial Technology (2020) Vol. 4, Iss. 1, pp. 111-138
Closed Access | Times Cited: 153
Ensemble of deep sequential models for credit card fraud detection
Javad Forough, Saeedeh Momtazi
Applied Soft Computing (2020) Vol. 99, pp. 106883-106883
Closed Access | Times Cited: 140
Combining Autoencoders and Deep Learning for Effective Fraud Detection in Credit Card Transactions
Mohammed Tayebi, Said El Kafhali
Operations Research Forum (2025) Vol. 6, Iss. 1
Closed Access | Times Cited: 2
Graph Neural Network for Fraud Detection via Spatial-Temporal Attention
Dawei Cheng, Xiaoyang Wang, Ying Zhang, et al.
IEEE Transactions on Knowledge and Data Engineering (2020) Vol. 34, Iss. 8, pp. 3800-3813
Closed Access | Times Cited: 108
Transaction Fraud Detection Based on Total Order Relation and Behavior Diversity
Lutao Zheng, Guanjun Liu, Chungang Yan, et al.
IEEE Transactions on Computational Social Systems (2018) Vol. 5, Iss. 3, pp. 796-806
Closed Access | Times Cited: 92
An intelligent payment card fraud detection system
Manjeevan Seera, Chee Peng Lim, Ajay Kumar, et al.
Annals of Operations Research (2021) Vol. 334, Iss. 1-3, pp. 445-467
Open Access | Times Cited: 86
Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection
Dawei Cheng, Sheng Xiang, Chencheng Shang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2020) Vol. 34, Iss. 01, pp. 362-369
Open Access | Times Cited: 81
Improved TrAdaBoost and its Application to Transaction Fraud Detection
Lutao Zheng, Guanjun Liu, Chungang Yan, et al.
IEEE Transactions on Computational Social Systems (2020) Vol. 7, Iss. 5, pp. 1304-1316
Closed Access | Times Cited: 78
Federated Meta-Learning for Fraudulent Credit Card Detection
Wenbo Zheng, Lan Yan, Chao Gou, et al.
(2020), pp. 4654-4660
Open Access | Times Cited: 75
Data poisoning attacks against machine learning algorithms
Fahri Anıl Yerlikaya, Şerif Bahtıyar
Expert Systems with Applications (2022) Vol. 208, pp. 118101-118101
Closed Access | Times Cited: 55
Improving Classification Performance in Credit Card Fraud Detection by Using New Data Augmentation
Emilija Strelcenia, Simant Prakoonwit
AI (2023) Vol. 4, Iss. 1, pp. 172-198
Open Access | Times Cited: 31
NUS: Noisy-Sample-Removed Undersampling Scheme for Imbalanced Classification and Application to Credit Card Fraud Detection
Honghao Zhu, MengChu Zhou, Guanjun Liu, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 2, pp. 1793-1804
Closed Access | Times Cited: 30
Fraud Feature Boosting Mechanism and Spiral Oversampling Balancing Technique for Credit Card Fraud Detection
Lina Ni, Jufeng Li, Huixin Xu, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 2, pp. 1615-1630
Closed Access | Times Cited: 29
Enhancing the Random Forest Model via Synthetic Minority Oversampling Technique for Credit-Card Fraud Detection
Fidelis Obukohwo Aghware, Arnold Adimabua Ojugo, Wilfred Adigwe, et al.
Journal of Computing Theories and Applications (2024) Vol. 1, Iss. 4, pp. 407-420
Open Access | Times Cited: 13
Credit Card Fraud Detection using ANN
S. Atchaya
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 2, pp. 170-175
Open Access | Times Cited: 9
Solving Misclassification of the Credit Card Imbalance Problem Using Near Miss
Nhlakanipho Michael Mqadi, Nalindren Naicker, Timothy T. Adeliyi
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-16
Open Access | Times Cited: 45
Enhancing Fra1ud Detection in Real Time using DataOps on Elastic Platforms
Ankur Mahida, Pradeep Chintale, Hrushikesh Deshmukh
International Journal of Scientific Research in Computer Science Engineering and Information Technology (2024) Vol. 10, Iss. 3, pp. 118-125
Open Access | Times Cited: 7
DaBO-BoostE: Enhanced Data Balancing via Oversampling Technique for a Boosting Ensemble in Card-Fraud Detection
Emakpor Augustine Otorokpo, Margaret Dumebi Okpor, Rume Elizabeth Yoro, et al.
Advances in Multidisciplinary & Scientific Research Journal Publication (2024) Vol. 12, pp. 45-66
Open Access | Times Cited: 6
Feature construction for fraudulent credit card cash-out detection
Yue Wu, Yunjie Xu, Jiaoyang Li
Decision Support Systems (2019) Vol. 127, pp. 113155-113155
Closed Access | Times Cited: 49
Intelligent UAV Identity Authentication and Safety Supervision Based on Behavior Modeling and Prediction
Changjun Jiang, Yu Fang, Peihai Zhao, et al.
IEEE Transactions on Industrial Informatics (2020) Vol. 16, Iss. 10, pp. 6652-6662
Closed Access | Times Cited: 41
Artificial neural network technique for improving prediction of credit card default: A stacked sparse autoencoder approach
Sarah A. Ebiaredoh-Mienye, Ebenezer Esenogho, Theo G. Swart
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2021) Vol. 11, Iss. 5, pp. 4392-4392
Open Access | Times Cited: 40
A Comparison of Data Sampling Techniques for Credit Card Fraud Detection
Abdulla Muaz, Manoj Jayabalan, V. Thiruchelvam
International Journal of Advanced Computer Science and Applications (2020) Vol. 11, Iss. 6
Open Access | Times Cited: 39
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