BSPNN: boosted subspace probabilistic neural network for email security
Artificial Intelligence Review
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Spam emails are causing major resource wastage by unnecessarily flooding the network links. Though many anti-spam solutions have been implemented, the Bayesian spam score approach looks quite promising. A proposal for spam detection algorithm is presented and its implementation using Java is discussed, along with its performance test results on two independent spam corpuses – Ling-spam and Enron-spam. We use the Bayesian calculation for single keyword sets and multiple keywords sets, along with its keyword contexts to improve the spam detection and thus to get good accuracy.