Web page classification based on k-nearest neighbor approach

Abstract

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 documentdocument 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.