A Model for Automatically Detecting and Blocking Pornographic Websites
Thuy-An Dinh, Tan‐Binh Ngo, Duc-Lung Vu · 2015
Preventing juveniles from accessing pornographic web pages remains a problem in Vietnam. The existing tools have failed to block these Vietnamese sites automatically and rely only on configuring black list and white list. In fact, the Vietnamese and English are different in both syntax and semantic, therefore, applying methods used for English into Vietnamese will definitely be much less effective. In this article, we present an automatic system that employs Naïve Bayes machine learning method to filter pornographic web pages in Vietnamese without impacting to users and system performance. The system contains 2 components: The classifier is researched and installed in server, and extension is integrated on the end user's browser. The entire system will be managed from 2 sides: server-side and client-side to gain the best result. In this article, our prime concern is to focus only on text, not image.