We propose anti-spam filtering methods for agglutinative languages in general and for
Turkish in particular. The methods are dynamic and are based on Artificial Neural Networks …

We propose dynamic anti-spam filtering methods for agglutinative languages in general and
for Turkish in particular, based on Artificial Neural Networks (ANN) and Bayesian filters. The …

In this paper, we propose spam e-mail filtering methods having high accuracies and low
time complexities. The methods are based on the n-gram approach and a heuristics which is …

In this paper, a Turkish anti-spam filtering is implemented to determine text-based Turkish
spam e-mails (junk e-mail or bulk e-mail). Since e-mails are extremely easy and cheap to …

The performance of two online linear classifiers—the Perceptron and Littlestone's Winnow—
is explored for two anti-spam filtering benchmark corpora—PU1 and Ling-Spam. We study …

Spam is one of the main problems in emails communications. As the volume of non-english
language spam increases, little work is done in this area. For example, in Arab world users …

In this paper, we present a comprehensive review of recent developments in the application
of machine learning algorithms to Spam filtering, focusing on both textual-and image-based …

The article gives an overview of some of the most popular machine learning methods
(Bayesian classification, k-NN, ANNs, SVMs) and of their applicability to the problem of …

Elecronic mail (E-mail) is an essential communication tool that has been greatly abused by
spammers to disseminate unwanted information (messages) and spread malicious contents …

This paper explores the use of the naive Bayes classifier as the basis for personalised spam
filters. Several machine learning algorithms, including variants of naive Bayes, have …