关键词: 网页分类, 隐含语义分析, 特征选择, KNN

Abstract: The feature vector of Chinese Web page is high dimension and very sparse for text categorization.How to reduce the dimensionality of feature space is a very key problem for practical text classification.In this paper a new method is described.The approach is to take advantage of latent semantic analysis and feature selection that use statistical methods.The K-Nearest Neighbor method is selected as the evaluating classifiers.The experimental result shows that the proposed method for Chinese Web page categorization to be promising.

Key words: Web Page categorization, latent semantic analysis, feature selection, KNN