Study of Chinese Text Classification Algorithm on Semantic Web

Chinese text automatic classification is an important research topic in the Chinese information processing field. The Chinese text classification method can be divided into two types: based on the extension of the classification method, and based on the semantic Web classification. The semantic Web is an extension of the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. So this paper present a algorithm of Chinese text classification on semantic Web. After getting keywords from the Web text, we get rid of ambiguity of the keywords. Then we get the semantic concept of the keywords base on how-net. Lastly, we classify the text after we integrate all the keywords semantic concept. We present experiments on different data set which demonstrates more effectiveness of our algorithm than traditional algorithm. It has been tested that this approach had good effect.