Spam filtering using a logistic regression model trained by an artificial bee colony algorithm

BK Dedeturk, B Akay - Applied Soft Computing, 2020 - Elsevier
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 filtering using integrated distribution-based balancing approach and regularized deep neural networks

A Barushka, P Hajek - Applied Intelligence, 2018 - Springer
Rapid growth in the volume of unsolicited and unwanted messages has inspired the
development of many anti-spam methods. Supervised anti-spam filters using machine …

Graph centrality based spam sms detection

A Ishtiaq, MA Islam, MA Iqbal, M Aleem… - … on Applied Sciences …, 2019 - ieeexplore.ieee.org
Short messages usage has been tremendously increased such as SMS, tweets and status
updates. Due to its popularity and ease of use, many companies use it for advertisement …

Machine Learning Techniques in Spam Filtering

A Barushka - 2020 - dk.upce.cz
The rapid growth of unsolicited and unwanted messages has inspired the development of
many anti-spam methods. Machine-learning methods such as Naive Bayes, support vector …

[引用][C] CHINONSO EZINNA EMMA-EBERE

C Ebere, C Fensch - 2017