Study Of The Information Content Securty Filter Method In WEB

The international information content security filter refers to identify the illegitimate text that include ill content and take out them. Along with the increase of the illegitimate text in WEB, content security filter has become a new study domain of information filter.Some key problems of content security filter have been studied in our paper, for example, the representation of train texts, identification of illegitimate text and the automatic learning to the new text. We also design an ICSF experimental system to implement all the functions that be mentioned above.Main work and innovation in this paper are:1.The characteristic of illegitimate text has been roundly analysis, and we summarize the content and vocable feature of illegitimate texts and put forward their formalized express.2.We realize content security filter by using the rule-based approaches. Based on large numbers of train examples, we adopt learning from examples approach which implement produce rules by using extended OCAT algorithm to realize classification of text. At the same time, we put forward rules for special word to calculate the credibility of text. At last, we combine the train rules and special word rules to identify the new documents.3.Two automatic learning algorithms are used respectively to improve the produced rules. At first we modify the logical rules according to the feedback information to improve the ability of identify of the new illegitimate content and to implement the increment learning. We also present an algorithm to automaticly pick-up new special words in new illegitimate document. Then the system can catch new status to the new illegitimate information.