With the flooding of pornographic information on the Internet, how to keep people away from that offensive information is becoming one of the most important research areas in network information security. Some applications which can block or filter such information are used. Approaches in those systems can be roughly classified into two kinds: metadata based and content based. With the development of distributed technologies, content based filtering technologies will play a more and more important role in filtering systems. Keyword matching is a content based method used widely in harmful text filtering. Experiments to evaluate the recall and precision of the method showed that the precision of the method is not satisfactory, though the recall of the method is rather high. According to the results, a new pornographic text filtering model based on reconfirming is put forward. Experiments showed that the model is practical, has less loss of recall than the single keyword matching method, and has higher precision.
A real-time visualization system based on meta-search engine for information retrieval is introduced. The essential motivation of this system is to organize retrieved documents in a visual way, by allowing users interact with the retrieval process of querying meta-search engines, in order to provide users a straightforward view of the distribution of the results. Instead of focusing on the extent to which the document objects are related with the query, the proposed system focuses on the differences among document objects. Document objects of the result set are distributed by calculating their pair-wise distances and clustering similar documents in a relatively nearby area.
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