Application Research of Support Vector Machine in Web Information Classification
Information retrieval is facing great challenge due to the explosion of the network scales. This makes more researchers focus on the issue of Web page classification technology. To facilitating user accurately locating information needed, applying binary decision tree into Support Vector Machine (SVM), a new SVM method based Web information classification algorithm has been introduced. Based on classifier composed by SVM-Decision Tree, a proposed approach was supported by the clustering method to solve the multi-category classification problem, reduces numbers of the training sample in SVM, and increases the classification speed and accuracy effectively.