Email Spam Detection using Natural Language Processing (NLP) and Deep Learning

1. AbdulNabi, Isra’A., and Qussai Yaseen. "Spam email detection using deep learning techniques." Procedia Computer Science 184 (2021): 853
(references)
2. Uddin, Mohammad Amaz, et al. "Explainabledetector: Exploring transformer-based language modeling approach for sms spam detection
with explainability analysis."(2024).
3. SHirvani, Ghazaleh, and Saeid Ghasemshirazi. "Advancing Email Spam Detection: Leveraging Zero-Shot Learning and Large Language
Models."(2025).
4. M. Yuan, Y. Huang, and Q. Lu, "BERT-based Spam Email Classification," in Proceedings of the IEEE International Conference on
Big Data, 2019, pp. 4342–4347..
5. Tida, Vijay Srinivas, and Sonya Hsu. "Universal spam detection using transfer learning of BERT model" (2022). Zavrak, Sultan, and Seyhmus
Yilmaz. "Email spam detection using hierarchical attention hybrid deep learning method." Expert Systems with Applications 233 (2023):
120977.
6. Labonne, Maxime, and Sean Moran. "Spam-t5: Benchmarking large language models for few-shot email spam detection." (2023)
7. asreen, Ghazala, et al. "Email spam detection by deep learning models using novel feature selection technique and BERT." Egyptian
Informatics Journal 26 (2024)
8. Sakkis, Georgios, et al. "Stacking classifiers for anti-spam filtering of e-mail."(2001).
9. Cormack, G. V. (2008).* Email Spam Filtering: A Systematic Review. Foundations and Trends in Information Retrieval