On the influence of traditional concept

the last one or two words of Chinese name usually has a certain instructions role to gender recognition.Gender recognition of person name can be used in natural language processing which is a specific application of Named Entity Recognition.Gender recognition method makes use of the structure and vocabulary information of Chinese personal name.The experiment on the basis of CRF is designed by constructing person name annotation set and selecting suitable feature model using NLP technology.Through the closed test on 231337 person names 89.30% accuracy is got which is about seven percentages higher than the bayes method.The experiment proves that the effect of the last name in gender recognition is higher than the role of the first name and the accuracy of gender recognition in female names is more higher than male names

about two or three percentages.Gender differences based on machine learning can be found from the names itself.The general principle of template design was proposed.