A hybrid correlation-based deep learning model for email spam classification using fuzzy inference system

Author:

Ayo Femi EmmanuelORCID,Ogundele Lukman Adebayo,Olakunle Solanke,Awotunde Joseph BamideleORCID,Kasali Funmilayo A.ORCID

Publisher

Elsevier BV

Subject

Modeling and Simulation,Applied Mathematics,Analysis,General Decision Sciences

Reference49 articles.

1. R.K. Kumar, G. Poonkuzhali, P. Sudhakar, Comparative study on email spam classifier using data mining techniques, in: Proceedings of the International MultiConference of Engineers and Computer Scientists, Vol. 1, 2012, pp. 14–16.

2. A review on machine learning techniques for image based spam emails detection;Abdullahi,2021

3. Y. Lin, (n.d.). How Many People Use Email in 2023? [2023 Update]. https://www.oberlo.com/statistics/how-many-people-useemail#:~:text=According%20to%20a%20study%20that,half%20of%20the%20global%20population.

4. Comparative study of classification algorithms for spam email detection;Sharaff,2016

5. Spam reduction by using E-mail history and authentication (SREHA);Yasin;Int. J. Comput. Netw. Inf. Secur.,2016

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