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All issues Volume 399 (2023) E3S Web Conf., 399 (2023) 04022 References
Open Access
Issue
E3S Web Conf.
Volume 399, 2023
International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
Article Number 04022
Number of page(s) 12
Section Computer Science
DOI https://doi.org/10.1051/e3sconf/202339904022
Published online 12 July 2023
  1. Alkhatib, Khalid I., Ahmad I. Al Aiad, Mothanna H. Almahmoud, and Omar N. Elayan. 2021. “Credit Card Fraud Detection Based on Deep Neural Network Approach.” In 2021 12th International Conference on Information and Communication Systems (ICICS). IEEE. https://doi.org/10.1109/icics52457.2021.9464555. [Google Scholar]
  2. Anita, C. S., P. Nagarajan, G. Aditya Sairam, P. Ganesh, and G. Deepakkumar. 2021. “Fake Job Detection and Analysis Using Machine Learning and Deep Learning Algorithms.” Revista Gestão Inovação E Tecnologias. https://doi.org/10.47059/revistageintec.v11i2.1701. [Google Scholar]
  3. Baraneetharan, E. 2022. “Detection of Fake Job Advertisements Using Machine Learning Algorithms.” September 2022. https://doi.org/10.36548/jaicn.2022.3.006. [Google Scholar]
  4. C. Mythilipriya, C. Mythilipriya, S. Priyadharshini, S. Karan, and Priyadharshini P. Sugantha. 2021. “Fake Website Prediction Using Random Forest.” 2021 Second International Conference on Electronics and the Sustainable Communication Systems in the fake news prediction (ICESC). https://doi.org/10.1109/icesc51422.2021.9532770. [Google Scholar]
  5. Dileep, M. R., A. V. Navaneeth, and M. Abhishek. 2021. “A Novel Approach for Credit Card Fraud Detection Using Decision Tree and Random Forest Algorithms.” In 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV). IEEE. https://doi.org/10.1109/icicv50876.2021.9388431. [Google Scholar]
  6. Hoti, Arber H., Mergim H. Hoti, Hamdi Hoti, and Armend Salihu. 2022. “Identifying Fake News Written on Albanian Language in Social Media Using Naive Bayes, SVM, Logistic Regression, Decision Tree and Random Forest Algorithms.” 2022 11th Mediterranean Conference on Embedded Computing (MECO). https://doi.org/10.1109/meco55406.2022.9797147. [Google Scholar]
  7. Keerthi Meghana, Sahitya, Jyothi Priyanka, and D. Sree Lakshmi. 2022. “Credit Card Fraud Identification Using Logistic Regression and Local Outlier Factor.” In 2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS). IEEE. https://doi.org/10.1109/icps55917.2022.00026. [Google Scholar]
  8. Krishna, M. Vamsi, and J. Praveenchandar. 2022. “Comparative Analysis of Credit Card Fraud Detection Using Logistic Regression with Random Forest towards an Increase in Accuracy of Prediction.” In 2022 International Conference on Edge Computing and Applications (ICECAA). IEEE. https://doi.org/10.1109/icecaa55415.2022.9936488. [Google Scholar]
  9. Kumar, M. Suresh, V. Soundarya, S. Kavitha, E.S. Keerthika, and E. Aswini. 2019. “Credit Card Fraud Detection Using Random Forest Algorithm.” In 2019 3rd International Conference on Computing and the Communications Technologies in the fraud detection (ICCCT). IEEE. https://doi.org/10.1109/iccct2.2019.8824930. [Google Scholar]
  10. Madhavi, Dr. D., and D. Madhavi. 2022. “Detection of Online Employment Scam Through Fake Jobs Using Random Forest Classifiers.” International Journal for Research in Applied Science and Engineering Technology. https://doi.org/10.22214/ijraset.2022.44384. [Google Scholar]
  11. Murugesan Sudhakar, and K.P. Kaliyamurthie. “ESTIMATION OF PRECISION IN FAKE NEWS DETECTION USING NOVEL BERT ALGORITHM AND COMPARISON WITH RANDOM FOREST.” https://doi.org/10.22541/au.165237518.82791368/v1. [Google Scholar]
  12. Parekh Prerak, Chirag Rana, Kunal Nalawade, and Surekha Dholay. 2021. “Credit Card Fraud Detection with Resampling Techniques.” In 2021 12th International Conference on Computing Communication and the Networking Technologies in credit card fraud detection (ICCCNT). IEEE. https://doi.org/10.1109/icccnt51525.2021.9579915. [Google Scholar]
  13. Pradhan Sasmita Kumari, N.V. Krishna Rao, N.M. Deepika, Putta Harish, M.A. Pawan Kumar, and Prem Sai Kumar. 2021. “Credit Card Fraud Detection Using Artificial Neural Networks and Random Forest Algorithms.” 2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA). https://doi.org/10.1109/iceca52323.2021.9676142. [Google Scholar]
  14. Ranparia Devsmit, Shaily Kumari, and Ashish Sahani. 2020. “Fake Job Prediction Using Sequential Network.” 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS). https://doi.org/10.1109/iciis51140.2020.9342738. [Google Scholar]
  15. Wang Tianyou, and Yucheng Zhao. 2022. “Credit Card Fraud Detection Using Logistic Regression.” In 2022 International Conference on Big Data, Information and Computer Network (BDICN). IEEE. https://doi.org/10.1109/bdicn55575.2022.00064. [Google Scholar]
  16. Yan Tianyang, Yuxin Li, and Jiaxu He. 2021. “Comparison of Machine Learning and Neural Network Models on Fraud Detection.” In 2021 IEEE International Conference on Artificial Intelligence and the Computer science and engineering Applications (ICAICA). IEEE. https://doi.org/10.1109/icaica52286.2021.9498212. [Google Scholar]

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