A dynamic weighted method with support vector machines for Chinese word segmentation

We explore how a dynamic weighted method with SVM works well for a Chinese word segmentation task. We set up two systems, System1 uses the uniform weight and we take it as our baseline system, System1 uses the dynamic weighted method as we proposed. We compare the performance of the two systems under different experiments conditions, and experiments results show that System2 got an outstanding performance in every condition we tested. It indicates that the dynamic weighted method we proposed has a stronger performance and can be used in many other SVM task such as chunking, POS and so on. At last, we describe a trick that can calculate the segmentation precision ratio and recall ratio for a segmentation task as soon as the end of the training or test process of a SVM procedure at essentially no extra cost.