Name
Abstract | ||
|---|---|---|
The problem of spam emails is still growing. Therefore, developing of algorithms which are able to solve this problem is also very active area. This paper presents two different algorithms for spam detection. The first algorithm is based on Bayesian filter, but it is improved using data compression algorithms in case that the Bayesian filter cannot decide. The second algorithm is based on document classification algorithm using Particle Swarm Optimization. Results of presented algorithms are promising. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CASoN.2012.6412413 | Computational Aspects of Social Networks |
Keywords | Field | DocType |
Bayes methods,data compression,document handling,e-mail filters,particle swarm optimisation,pattern classification,unsolicited e-mail,Bayesian filter,PSO,data compression algorithm,document classification algorithm,particle swarm optimization,spam email detection,Bayesian filter,data compression,e-mail,particle-swarm optimization,similarity,spam | Particle swarm optimization,Document classification,Compression (physics),Data mining,Computer science,Artificial intelligence,Document handling,Data compression,Bayesian filtering,Machine learning | Conference |
ISSN | ISBN | Citations |
2155-7047 | 978-1-4673-4793-8 | 0 |
PageRank | References | Authors |
0.34 | 17 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Prilepok | 1 | 32 | 6.45 |
| Tomas Jezowicz | 2 | 0 | 0.34 |
| Jan Platos | 3 | 286 | 58.72 |
| Václav Snasel | 4 | 1261 | 210.53 |