Spam filtering using classification algorithms
Data(s) |
01/01/2008
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Resumo |
This thesis proposes an innovative adaptive multi-classifier spam filtering model, with a grey-list analyser and a dynamic feature selection method, to overcome false-positive problems in email classification. It also presents additional techniques to minimize the added complexity. Empirical evidence indicates the success of this model over existing approaches. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Deakin University, Faculty of Science and Technology, School of Engineering and Information Technology |
Palavras-Chave | #Spam filtering (Electronic mail) #Spam (Electronic mail) - Prevention #Electronic mail systems - Standards #Internet - Security measures |
Tipo |
Thesis |