The effects of domain knowledge relations on domain text classification

The text classification usually uses the statistical method to select characteristic. When it is carried out in different domains, the special interior knowledge relationships between domains will not be considered. In this paper, a new text classification model is proposed, which is based on the domain knowledge relations. This model adopts the support vector machine study algorithm, combine statistic samples and domain terminology to make up classification feature space, and calculate the similarity between domain conceptions, so that classification characteristic is entrusted with certain weight, realizing domain text classification. The new model has been made use of to carry out a text classification experiment about YunNan travel domain and non-travel domain. The result shows that domain knowledge has great effects on domain text classification and the accuracy of classification has been improved by 4 percentage compared with the improved TFIDF method.