Abstract:

This paper proposes a new method of feature extraction of SMS for better spam message filtering.The method uses the latest results and tools of Word2vec based on deep learning theory.With the content and structure characteristics of Chinese short messages in mind,an algorithm of Vectoring SMS is designed based on this tool.The algorithm can effectively match each text message with a vector.The classification's experiments on the spam messages are carried out using the proposed algorithm on the deep belief networks.The results show that the performance of the proposed algorithm is improved by 5% compared with the previously reported results.

Key words: deep belief nets;deep learning;short messages;vectoring