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A review of machine learning approaches to spam filtering
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 …
Binary PSO with mutation operator for feature selection using decision tree applied to spam detection
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 …
false positive error of mislabeling nonspam as spam. First, we used the wrapper-based …
Rough sets for spam filtering: Selecting appropriate decision rules for boundary e-mail classification
Nowadays, spam represents an extensive subset of the information delivered through
Internet involving all unsolicited and disturbing communications received while using …
Internet involving all unsolicited and disturbing communications received while using …
Improved email spam detection model with negative selection algorithm and particle swarm optimization
The adaptive nature of unsolicited email by the use of huge mailing tools prompts the need
for spam detection. Implementation of different spam detection methods based on machine …
for spam detection. Implementation of different spam detection methods based on machine …
Using evolutionary computation for discovering spam patterns from e-mail samples
One of the most relevant problems affecting the efficient use of e-mail to communicate
worldwide is the spam phenomenon. Spamming involves flooding Internet with undesired …
worldwide is the spam phenomenon. Spamming involves flooding Internet with undesired …
Concept drift in e-mail datasets: An empirical study with practical implications
Internet e-mail service emerged in the late seventies to implement fast message exchanging
through computer networks. Network users immediately discovered the value of this service …
through computer networks. Network users immediately discovered the value of this service …
A local-concentration-based feature extraction approach for spam filtering
Y Zhu, Y Tan - IEEE Transactions on Information Forensics and …, 2010 - ieeexplore.ieee.org
Inspired from the biological immune system, we propose a local concentration (LC)-based
feature extraction approach for anti-spam. The LC approach is considered to be able to …
feature extraction approach for anti-spam. The LC approach is considered to be able to …
SDAI: An integral evaluation methodology for content-based spam filtering models
Tragedy of Commons Theory introduced by Hardin (1968) revealed how shared and limited
resources get completely depleted as effect of human behaviour. By analogy, common …
resources get completely depleted as effect of human behaviour. By analogy, common …
Integrated radio frequency identification and wireless sensor network architecture for automated inventory management and tracking applications
ML McKelvin Jr, ML Williams, NM Berry - Proceedings of the 2005 …, 2005 - dl.acm.org
We provide a system architecture that applies radio frequency identification and wireless
sensor network technologies to automate inventory management and tracking of commercial …
sensor network technologies to automate inventory management and tracking of commercial …
[PDF][PDF] Immune based feature selection for opinion mining
Opinions about a particular product, service or person are communicated effectively through
online media such as Facebook, MySpace and Twitter. Unfortunately only a few researchers …
online media such as Facebook, MySpace and Twitter. Unfortunately only a few researchers …