Implementation of Mail Classification Using Neural Networks of the Second Type Spline Weight Functions

Abstract:

How to effectively filter out spam is a topic worthy of further study for the growing proliferation of spam. The main purpose of this paper is to apply a new neural network algorithm to the classification of spam. In this paper, we introduce a second type of spline weight function neural network algorithm, as well as e-mail feature extraction and vectorization, and then introduced the mail sorting process. Experiments show that it can get a relatively high accuracy and recall rate on the spam classification. Therefore, with this new algorithm, we can achieve better classification results.

• Periodical: Applied Mechanics and Materials (Volumes 513-517)
• Pages: 687-690
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.513-517.687
• Online since: February 2014
• Authors: Dai Yuan Zhang*, Lei Yang
• Keywords: Algorithm (GA), Email Classification, Feature Extraction, Neural Network (NN), Spline Weight Function

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