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  1. In this paper we review some of the most popular machine learning methods (Bayesian classification, k-NN, ANNs, SVMs, Artificial immune system and Rough sets) and of their applicability to the problem of spam Email classification.

  2. 11 Μαΐ 2022 · PDF | Spam emails have been traditionally seen as just annoying and unsolicited emails containing advertisements, but they increasingly include scams,... | Find, read and cite all the...

  3. 10 Ιουν 2019 · We present a systematic review of some of the popular machine learning based email spam filtering approaches. Our review covers survey of the important concepts, attempts, efficiency, and the...

  4. 23 Ιουν 2008 · This paper analyzes to what extent Bayesian filtering techniques used to block email spam, can be applied to the problem of detecting and stopping mobile spam, and demonstrates that Bayesian filters can be effectively transferred from email to SMS spam.

  5. 7 Οκτ 2020 · Based on those structures (discovered solely by processing sighted spam mail), we propose a family of new spam-blocking techniques exploiting group membership of perceived spam sources.

  6. 1 Ιουν 2019 · They discussed the fundamentals of e-mail spam filtering, the changing nature of spam, the tricks of spammers to evade spam filters of e-mail service providers (ESPs), and also examined the popular machine learning techniques used in combating the menace of spam.

  7. 3 Σεπ 2018 · detect and lter spam emails. We present a systematic review of some of the popular machine learning based fi email spam ltering approaches. Our review covers survey of the important concepts, attempts, ef ciency, and the fi fi research trend in spam ltering.

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