WebAngels Filter: A Violent Web Filtering Engine Using Textual and Structural Content-Based Analysis

摘要

The development of the Web has been paralleled by the proliferation of harmful Web pages content. Using Violent Web page as a case study, we review some existing solutions, then we propose a violent Web content detection and filtering system called "WebAngels filter" which uses textual and structural analysis. "WebAngels filter" has the advantage of combining several data mining algorithms for Web site classification. We present a comparative study of different data mining techniques to block violent contentWeb pages. Also, we discuss how the combination learning based methods can improve filtering performances. Our results show that it can detect and filter violent content effectively.