The Antispam Full-text Segmentation Technology Implementation And Application Of Research

With wide application of email, spams, acting as the carrier of business advertisements, the malicious programs or some sensitive mails, are more and more fiercely threatening the safety of the computer systems and the lives of people. Anti-spam problem has become an international, significantant and practical topic now .Now, the most popular method in spam filter is divided into two category, one is based on regular and the other is based on statistic.It prevent the spam from Internet through setting filter rules or the black list and so on. But the biggest disadvantage of these technologies is that they are not of intelligence and self-adaption and the problem of data redundancies and veracity is stand out.In order to resolve these conflicts, the thesis brings forward an approach for Chinese lexical analysis using cascaded hidden Markov model (CHMM), which aims to incorporate Chinese word segmentation, includes speech tagging, disambiguation and unknown words recognition into an integrated theoretical frame. It may markedly reduce data redundancies and improve the veracity .The thesis mainly discussed how to keep away use full filter which depend on what reason bring the spam,send mechanism,Chinese lexical analysis,hidden Markov model. And also give result analyze based on test.