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 …

In this paper, we proposed a novel spam detection method that focused on reducing the
false positive error of mislabeling nonspam as spam. First, we used the wrapper-based …

Email spam is a serious problem that annoys recipients and wastes their time. Machine-
learning methods have been prevalent in spam detection systems owing to their efficiency in …

Spam represents a genuine irritation for email users, since it often disturbs them during their
work or free time. Machine learning approaches are commonly utilized as the engine of …

So fast, so cheap, so efficient, Internet is nowadays incontestably communication mean of
choice for personal, business and academic purposes. Unfortunately, Internet has not only …

In this paper, we examine the use of keywords in text categorization with SVM. In contrast to
the usual belief, we reveal that using keywords instead of all words yields better …

Owing to the rapid growth of the World Wide Web, the number of documents that can be
accessed via the Internet explosively increases with each passing day. Considering news …

The growth of email users has resulted in the dramatic increasing of the spam emails during
the past few years. In this paper, four machine learning algorithms, which are Naïve …

Phishing emails called spam have created a need for reliable and intelligent spam filters.
Machine-learning techniques are effective, but current methods such as Logistic Regression …

Preprocessing is an important task and critical step in information retrieval and text mining.
The objective of this study is to analyze the effect of preprocessing methods in text …