Filtering Chinese Spam-mail Based on LVQ2 Neural Network and Decision Tree Classifying
Yuxuan Wang · Jisuanji gongcheng · 2005
The great economic losses as well as the arduous work on information processing brought about by spam-mail becomes a world-wide problem. At present, some effective ways of filtering spam-mail are based on Bayes probality model. However, the complexity of Chinese and the decertfulness of Bayes algorithm make it difficult to filter Chinese spam-mail. In this case, a new algorithm based on LVQ2 neural network and decision tree classifying is put forward. The result of experiment proves that this algorithm can filter over 98% of the Chinese spam-mail.