Salehi, Saber and Selamat, Ali (2011) Hybrid simple artificail immune system (SAIS) ans particle swarm optimization (PSO) for spam detection. In: 2011 5th Malaysian Software Engineering Conference (MYSEC).
Full text not available from this repository.
Official URL: http://ieeexplore.ieee.org.ezproxy.utm.my/document...
Abstract
Spam detection is a significant problem which considered by many researchers by various developed strategies. Among many others, simple artificial immune system is one of those being proposed. There is a deficiency in number of optimization methods in simple artificial immune system (SAIS). This problem can be solved and eliminated using other optimization methods besides mutation. In this research, SAIS was hybridized by particle swarm optimization (PSO) for optimizing the performance of SAIS for spam filtering. PSO was used with mutation to reinforce the immune system's searches to find the best class in exemplar for classification. Achieved results represent the Hybrid SAIS and PSO is superior to that of a SAIS.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Immune system, Classification algorithms, Electronic mail, Training data, Accuracy, Optimization, Filtering, Particle Swarm Optimization (PSO), Spam, Simple Artificial Immune System (SAIS) |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Others |
| ID Code: | 45925 |
| Deposited By: | Haliza Zainal |
| Deposited On: | 10 Jun 2015 03:01 |
| Last Modified: | 29 Aug 2017 01:17 |
Repository Staff Only: item control page
