Abstract
The World Wide Web is growing at an uncontrollable rate. Hundreds of thousands of web sites appear every day, with the added challenge of keeping the web directories up-to-date. Further, the uncontrolled nature of web presents difficulties for Web page classification. As the number of Internet users is growing, so is the need for classification of web pages with greater precision in order to present the users with web pages of their desired class. However, web page classification has been accomplished mostly by using textual categorization methods. Herein, we propose a novel approach for web page classification that uses the HTML information present in a web page for its classification. There are many ways of achieving classification of web pages into various domains. This paper proposes an entirely new dimension towards web page classification using Artificial Neural Networks (ANN). Index Terms: World Wide Web, Web page classification, textual categorization, HTML, Artificial Neural Networks, ANN.
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