本文借鉴邮件过滤算法，通过对中文邮件语料的研究，提出了建设一个基于平凡算法和规则相结合的、具有自适应能力的、实用的邮件分类系统。
So this thesis brings forward to construct a self-adaptive and practical mail classification system based on the integration of normal algorithm with regulations after studying Chinese mail corpus.
在声音邮件方面，那些依赖于报文索引的系统常常依赖于日期标志进行报文分类。
On the voice mail side, systems that rely on message indexing often rely on date stamps to sort messages.
在系统运行初期，由用户指定邮件的类别，系统根据用户的分类建立用户兴趣模型。
In the initial stage of system, user appoints the classification of every mail and system set up a user model according to the classification.
本文提出了一种基于贝叶斯方法的电子邮件分类器，讨论了其基本思想，给出了实现的系统结构。
This paper proposes a Bayesian method based E-mail classifier, discusses the idea and gives the system structure.
该文对现有电子邮件系统中存在的安全性、垃圾邮件、邮件分类、信箱命名资源等问题进行了分析。
In current E-mail system, there are some problem which must be solved, such as the safety of E-mail, junk E-mail, classification of E-mail, name resource and so on.
系统采用黑白名单过滤、邮件特征过滤和贝叶斯分类相结合的三层过滤技术，并通过用户反馈机制降低误报率。
The filtering system was built up with multi-layer filtering technology as blacklist technology, characteristic filtering, Naive Bayesian, and user feedback mechanism.
该文对现有电子邮件系统中存在的安全性、垃圾邮件、邮件分类、信箱命名资源等问题进行了分析。
The authors analyze the essence of some existing algorithms of junk E-mail filtering rules and give the way to represent an E-mail as a transaction.
该文对现有电子邮件系统中存在的安全性、垃圾邮件、邮件分类、信箱命名资源等问题进行了分析。
The authors analyze the essence of some existing algorithms of junk E-mail filtering rules and give the way to represent an E-mail as a transaction.
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