A high accuracy rate spam recognition method

Kolmogorov complexity theory was adopted to describe the characteristics of emails, information distance was adopted to evaluate the similarity between emails, support vector machine (SVM) method was adopted to classify the emails, and thus a high accuracy rate spam recognition method was proposed. Compared with traditional spam recognition methods, the proposed method features simplicity and efficiency, and precisely embodies the characteristics of spam, without dividing each junk mail and analyzing its header and text separately. The resulting experiments show that the accuracy rate of email classification is up to 99% for text email, and this method effectively enhances the accuracy rate of spam recognition.