A new method of Chinese personal names recognition based on TBL

Recognition of Chinese personal name is a difficult and challenging task in unknown words recognition. In this paper, we proposed a method of Chinese name recognition based on Support Vector Machines (SVM) and transformation-based error-driven learning. Using the transformation-based learning approach to correct the identification results of SVM. Transformation rules effectively deal with the special cases of language phenomenon and improve the performance of SVM. Experiments show that the method is effective. In open test, the precision, recall, and F-measure are improved.