An efficient text filter for adult Web documents

The openness of the Web allows any users to access almost any type of information. However, some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal pornographic sites can do ordinary people´s mental health harm. In this paper, we propose a new criterion and divide contents of Web documents into 4 grades. We use a hierarchical way of filtering texts. At first, we filter off 0-grade texts contain no adult contents using a pattern matching algorithm, and classify 1-grade, 2-grade and 3-grade texts using a machine learning algorithm