1. Zhang, Y., Wang, S.: Spam detection via feature selection and decision tree. J. Comput. Theor. Nanosci. 5(2), 726–730 (2012). https://www.researchgate.net/publiction/272272678_Spam_Detection_via_Feature_Selection_and_Decision_Tree
2. Soni, A.N.: Spam-e-mail-detection-using-advanced-deep-convolution-neuralnetwork-algorithms. J. Innov. Dev. Pharmaceut. Tech. Sci. 2(5), 74–80 (2019). ISSN 2581–6934. https://jidps.com/wp-content/uploads/2019/05/Spam-e-mail-detection-using-advanced-deep-convolution-neural-network-algorithms.pdf
3. Mani, S., Gunasekaran, G., Geetha, S.: Email spam detection using gated recurrent neural network. Int. J. Prograssive Res. Eng. Manag. Sci. 03(04), 90–99 (2023). e-ISSN: 2583–1062. https://www.ijprems.com/uploadedfiles/paper/issue_4_april_2023/30834/final/fin_ijprems1680790618.pdf
4. Ma, T.M., Thida, A., Yamamori, K.: A comparative approach to naive bayes classifier and support vector machine for email spam classification. In: 2020 IEEE 9th Global Conference onConsumer Electronics (GCCE) (2020). https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9291921&casa_token=7wRO6IPe0WsAAAAA:fIl32tDxoM3wawPW89mCNZ4ufqN5aMbVPfhTnSWF1udZHCWU-F2mnrZgdre_RJrjb_PbOMHraFJ
5. Johnson, J.: Number of sent and received e-mails per day worldwide from 2017 to 2025 (2021). https://www.statista.com/statistics/456500/daily-number-of-e-mails-worldwide/. Accessed 20 Jan 2022