该技术通过引入用户反馈机制，使用改进的朴素贝叶斯方法，构建面向特定用户的过滤器，从而进行垃圾邮件过滤。
By introducing the novel users' feedback mechanism, the technique adopts an improved Na? Ve Bayesian approach to construct classifiers for specific users to fulfill spam filtering.
基于朴素贝叶斯分类方法的实验表明，提出的方法能够有效提高中文文本的分类准确率。
The experiment of Naive Bayes classification indicates that this method can effectively improve classification precision of Chinese texts.
围绕着分类挖掘中的隐私保护问题展开研究，给出了一种基于数据处理和特征重构的朴素贝叶斯分类中的隐私保护方法。
This paper focuses on privacy preserving classification, and presents a privacy preserving Naive Bayes classification approach based on data randomization and feature reconstruction.
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