Web Page Classification using Modified Naïve Bayesian Approach

This paper introduces the concept of a classification tool for Web pages called WebClassify, which uses modified naive Bayesian algorithm with multinomial model to classify pages into various categories. The tool starts the classification from downloading training Web text from Internet, preparing the hypertext for mining, and then storing Web data in a local database. The paper also gives an account of choosing naive Bayesian approach over other approaches for Web text mining. The experimental results along with the classification accuracy analysis with increasing vocabulary size, is also shown