A Novel Web Page Filtering System by Combining Texts and Images

Abstract

With the rapid development of the Internet, people benefit much from the sharing of information. Meanwhile, the WWW era is a double-edged sword which spreads harmful and erotic content widely. In this paper, a new statistical approach has been exploited by combining the results of two or more different classification methods using our filtering system. We first briefly introduce the classification of discrete texts, continuous texts and images separately, and then describe the specific way we have been exploring to merge the text and image classification result. Also there is a section illustrating our system framework. Finally we assess our method by demonstrating the experimental results and comparing it to some common-used filtering methods