Web page classification based on k-nearest neighbor approach
Oh‐Woog Kwon, Jong-Hyeok Lee · 2000
Automatic categorization is the only viable method to deal with the scaling problem of the World Wide Web. In this paper, we propose a Web page classifier based on an adaptation of k-Nearest Neighbor (k-NN) approach. To improve the performance of k-NN approach, we supplement k-NN approach with a feature selection method and a term-weighting scheme using markup tags, and reform document-document similarity measure used in vector space model. In our experiments on a Korean commercial Web directory, our proposed methods in k-NN approach for Web page classification improved the performance of classification.