By utilizing part-of-speech analysis on Chinese Deep Web query result, a Deep Web semantic annotation method is proposed based on Chinese part-of-speech and domain knowledge.

For Chinese words segmentation,a module which is based on word library and uses the positive direction maximum matching algorithm was presented.

Chinese WEB documents classification involves to the documents automatic capture, the information processing and the extraction, the automatic sorting and so on, this article realizes a open style Chinese WEB documents automatic sorting system, and has applied several improvement algorithms in the system module, in the main solution present information retrieval involves when Chinese participle .

The computer may very easily understand English word, but Chinese sentence which is composed by the word, which can be understood through Chinese participle technology.

It returned to the first results of the Chinese participle and fully tap its semantic information use CC4 neural networks to judge the he rele-vant web page to re-sort the results,and a good solution integrated search engine does not prevail in the search results accurate information stagnant.

To improve the preprocessing performance for anti-spam and to search for phrases more efficiently, this paper creatively constructed an indexing dictionary based on hash algorithm, and designed a method of Chinese phrase segmentation based on this indexing dictionary aiming at anti-Chinese-spam.

CRFs-based Chinese word segmentation method with character position probability feature;

Research of Chinese word segmentation system applies in professional search engine;

Chinese Word Segmentation Method Based on Dictionary and Frequency of the Words;