NamePrism is a non-commercial nationality/ethnicity classification tool that aims to support academic research, e.g. sociology and demographic studies. In this project, we learn name embeddings for name parts (first/last names) and classify names to 39 leaf nationalities and 6 U.S. ethnicities.
Aug 25, 2017 · Existing name-based nationality classifiers use name substrings as features and are trained on small, unrepresentative sets of labeled names, ...
We exploit the phenomena of homophily in communication patterns to learn name embeddings, a new representation that encodes gender, ethnicity, and nationality ...
Existing name-based nationality classifiers use name sub- strings as features and are trained on small, unrepresentative sets of labeled names, typically ...
This work designs a fine-grained nationality classifier covering 39 groups representing over 90% of the world population and exploits the phenomena of ...
Existing name-based nationality classifiers use name substrings as features and are trained on small, unrepresentative sets of labeled names, typically ...
Jun 10, 2020 · The datasets we used were from GitHub (github.com/d4em0n/nationality-classify). ... Name-ethnicity classification and ethnicity-sensitive name ...
In this project, we learn name embeddings for name parts (first/last names) and classify names to 39 leaf nationalities and 6 U.S. ethnicities.
A first sample of 70 000 names was processed by NamePrism nationality and ethnicity classifiers, as well as NamSor Origin and Diaspora classifiers.
We propose a recurrent neural network based model which predicts nationalities of each name using automatic feature extraction. Evaluation of Olympic record ...