Web Page Classification based on Semi-supervised Naive Bayesian EM Algorithm

摘要：

Web Classification is one of the hot researches in Web mining field. Within the exploded Internet information circumstance, most pages are unlabeled. This paper has proposed a Naive Bayesian EM algorithm classification method based on the feature of Semisupervised machine learning. The method used Hierarchical Clustering EM framework to train Naive Bayesian Classifier iteratively. The result of the experiment proved that the method introduced in the paper shows good effect of Web classification.

关键词： Web page classification web mining Semi supervised Hierarchical Clustering

作者: Wang Zhixing Chen Shaohong

作者单位: Computer Center East China Normal University Shanghai,China

会议类型: 国际会议

会议名称: 2011 2nd International Conference on Data Storage and Data Engineering(DSDE 2011)(2011年第二届数据存储与数据工程国际会议)

会议地点: 西安

会议语种:英文

页码: 242-245

在线出版日期: 2011-05-13（万方平台首次上网日期，不代表论文的发表时间）