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 …
of machine learning algorithms to Spam filtering, focusing on both textual-and image-based …
Behavior-based spam detection using a hybrid method of rule-based techniques and neural networks
CH Wu - Expert systems with Applications, 2009 - Elsevier
Earlier methods on spam filtering usually compare the contents of emails against specific
keywords, which are not robust as the spammers frequently change the terms used in …
keywords, which are not robust as the spammers frequently change the terms used in …
Automated text classification using a dynamic artificial neural network model
M Ghiassi, M Olschimke, B Moon, P Arnaudo - Expert Systems with …, 2012 - Elsevier
Widespread digitization of information in today's internet age has intensified the need for
effective textual document classification algorithms. Most real life classification problems …
effective textual document classification algorithms. Most real life classification problems …
[PDF][PDF] Overview of textual anti-spam filtering techniques
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 …
spammers to disseminate unwanted information (messages) and spread malicious contents …
A weak-region enhanced Bayesian classification for spam content-based filtering
This article proposes an improved Bayesian scheme by focusing on the region in which
Bayesian may fail to correctly identify labels and improve classification performance by …
Bayesian may fail to correctly identify labels and improve classification performance by …
Adding robustness to support vector machines against adversarial reverse engineering
Many classification algorithms have been successfully deployed in security-sensitive
applications including spam filters and intrusion detection systems. Under such adversarial …
applications including spam filters and intrusion detection systems. Under such adversarial …
Automatic thesaurus construction for spam filtering using revised back propagation neural network
H Xu, B Yu - Expert Systems with Applications, 2010 - Elsevier
Email has become one of the fastest and most economical forms of communication. Email is
also one of the most ubiquitous and pervasive applications used on a daily basis by millions …
also one of the most ubiquitous and pervasive applications used on a daily basis by millions …
基于信息增益的文本特征选择方法
任永功， 杨荣杰， 尹明飞， 马名威 - 计算机科学, 2012 - cqvip.com
在类和特征分布不均时, 传统信息增益算法的分类性能急剧下降. 针对此不足,
提出一种基于信息增益的文本特征选择方法(TDpIG). 首先对数据集按类进行特征选择 …
提出一种基于信息增益的文本特征选择方法(TDpIG). 首先对数据集按类进行特征选择 …
A novel online and non-parametric approach for drift detection in big data
M Bhaduri, J Zhan, C Chiu, F Zhan - IEEE Access, 2017 - ieeexplore.ieee.org
A sizable amount of current literature on online drift detection tools thrive on unrealistic
parametric strictures such as normality or on non-parametric methods whose power …
parametric strictures such as normality or on non-parametric methods whose power …
Adaptive learning rate for online linear discriminant classifiers
LI Kuncheva, CO Plumpton - … : Joint IAPR International Workshop, SSPR & …, 2008 - Springer
We propose a strategy for updating the learning rate parameter of online linear classifiers for
streaming data with concept drift. The change in the learning rate is guided by the change in …
streaming data with concept drift. The change in the learning rate is guided by the change in …