Machine learning for email spam filtering: review, approaches and open research problems

EG Dada, JS Bassi, H Chiroma, AO Adetunmbi… - Heliyon, 2019‏ - cell.com
The upsurge in the volume of unwanted emails called spam has created an intense need for
the development of more dependable and robust antispam filters. Machine learning …

A review of machine learning approaches to spam filtering

TS Guzella, WM Caminhas - Expert Systems with Applications, 2009‏ - Elsevier
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 …

[کتاب][B] Recommender systems: an introduction

D Jannach, M Zanker, A Felfernig, G Friedrich - 2010‏ - books.google.com
In this age of information overload, people use a variety of strategies to make choices about
what to buy, how to spend their leisure time, and even whom to date. Recommender …

Mining data with random forests: A survey and results of new tests

A Verikas, A Gelzinis, M Bacauskiene - Pattern recognition, 2011‏ - Elsevier
Random forests (RF) has become a popular technique for classification, prediction, studying
variable importance, variable selection, and outlier detection. There are numerous …

An improved K-nearest-neighbor algorithm for text categorization

S Jiang, G Pang, M Wu, L Kuang - Expert Systems with Applications, 2012‏ - Elsevier
Text categorization is a significant tool to manage and organize the surging text data. Many
text categorization algorithms have been explored in previous literatures, such as KNN …

Classification of phishing email using random forest machine learning technique

AA Akinyelu, AO Adewumi - Journal of Applied Mathematics, 2014‏ - Wiley Online Library
Phishing is one of the major challenges faced by the world of e‐commerce today. Thanks to
phishing attacks, billions of dollars have been lost by many companies and individuals. In …

A brief survey on anonymization techniques for privacy preserving publishing of social network data

B Zhou, J Pei, WS Luk - ACM Sigkdd Explorations Newsletter, 2008‏ - dl.acm.org
Nowadays, partly driven by many Web 2.0 applications, more and more social network data
has been made publicly available and analyzed in one way or another. Privacy preserving …

Investigating the effect of dataset size, metrics sets, and feature selection techniques on software fault prediction problem

C Catal, B Diri - Information Sciences, 2009‏ - Elsevier
Software quality engineering comprises of several quality assurance activities such as
testing, formal verification, inspection, fault tolerance, and software fault prediction. Until …

A novel hybrid whale optimization algorithm with flower pollination algorithm for feature selection: Case study Email spam detection

H Mohammadzadeh… - Computational …, 2021‏ - Wiley Online Library
Feature selection (FS) in data mining is one of the most challenging and most important
activities in pattern recognition. In this article, a new hybrid model of whale optimization …

Email spam: A comprehensive review of optimize detection methods, challenges, and open research problems

EH Tusher, MA Ismail, MA Rahman, AH Alenezi… - IEEE …, 2024‏ - ieeexplore.ieee.org
Nowadays, emails are used across almost every field, spanning from business to education.
Broadly, emails can be categorized as either ham or spam. Email spam, also known as junk …