Study on the construction of domain text classification model with the help of domain knowledge

Traditional text classification model uses statistical methods to obtain features. But in the aspect of discrimination domain and non-domain text category, domain knowledge relations havenpsilat been taken account of in these methods. A domain text classification model was presented in this paper. This model used the support vector machine learning algorithm, gained domain classification feature words through statistic and union domain words, structured domain classification feature space. With the help of domain knowledge relations, computed relevance between domain concepts, got domain classification feature weight. Finally domain text classification was realized. An experiment in the Yunnan tourism domain was carried on to confirm that domain knowledge relations have a good influence on the domain text classification. The classification accuracy rate has been increased 0.04 than improved TFIDF method.