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In the last decade spam detection has been addressed as a text classification or categorization problem. In this paper we propose a new dynamic weighted voting method based on the combination of clustering and weighted voting, and apply it to the task of spam filtering. In order to classify a new sample, it first compares with all cluster centroids and its similarity to each cluster is identified; Classifiers in the vicinity of the input sample obtain greater weight for the final decision of the ensemble. The evaluation shows that the algorithm outperforms pure SVM.
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on (Volume:2 )
Date of Conference: 20-22 Dec. 2008