Hybrid simple artificial immune system (SAIS) and particle swarm optimization (PSO) for spam detection
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 pro...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2011
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| Online Access: | http://eprints.utm.my/id/eprint/45926/ http://dx.doi.org/10.1109/MySEC.2011.6140655 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | 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. |
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