摘要
本文介绍了设计的一个网页自动分类系统。介绍了预处理 ,批量训练 ,特征选择 ,在线测试和重归档等模块的设计过程。系统采用有指导的学习方法 ,选取 Naive Bayes作分类模型和信息增益作为特征提取方法。测试结果表明 。
A Web page automatic categorization system presents in this paper.It introudes the main module of the system including preprocessing,batch training,feature selection,online test and refiling.The system adopts supervised learning,Naive Bayes as the categorization model and information gain as the feature selection.The test results show that it can get good precision.
出处
《计算技术与自动化》
2002年第1期58-61,共4页
Computing Technology and Automation
