The Chinese Web Page Filtering System Based On Content Security

With the further development of Internet, in which is full of a great amount of legal and illegal information, the content information has already been a new member in security field. To offer the user of Internet healthy and secure information, it is necessary to filter out the dirty web pages. Despite many relevant technologies appearing the content-based Chinese web page, filtering technology remains to be improved owing to the particularity of Chinese language.Two pivotal technologies, Chinese word segmentation technology and filtering technology have been discussed after the content security of information and the present development of Chinese web filter are analyzed. Based on the former discussion, a Chinese word segmentation system with the ability of lexical-acquisition was proposed, which has improved performances than traditional systems. At the same time, this thesis proposes two filtering algorithms using Probability Model and Vector Space Model, thus constructing an effective web page filter based on the advantages of these two algorithms. Finally, on the basis of designed model above, the general designing, implementation and testing of the Chinese web page filtering system are accomplished.The further revised performances of the Chinese web page filtering system prove true with the aid of the improved accuracy of Chinese word segmentation and filter procedures.