Naive Bayes Web Page Classification with HTML Mark-Up Enrichment

Abstract

In text and Web page classification, Bayesian prior probabilities are usually based on term frequencies, term counts within a page and among all the pages. However, new approaches in Web page representation use HTML mark-up information to find the term relevance in a Web page. This paper presents a naive Bayes Web page classification system for these approaches