Name Nationality Classification with Recurrent Neural Networks
Jinhyuk Lee, Hyunjae Kim, Miyoung Ko, Donghee Choi, Jaehoon Choi, Jaewoo Kang · 2017
Personal names tend to have many variations differing from country to country. Though there exists a large amount of personal names on the Web, nationality prediction solely based on names has not been fully studied due to its difficulties in extracting subtle character level features. We propose a recurrent neural network based model which predicts nationalities of each name using automatic feature extraction. Evaluation of Olympic record data shows that our model achieves greater accuracy than previous feature based approaches in nationality prediction tasks. We also evaluate our proposed model and baseline models on name ethnicity classification task, again achieving better or comparable performances. We further investigate the effectiveness of character embeddings used in our proposed model.