Automated user language detection for content selection

A method, comprising:

• receiving, by a data processing system having one or more processors, from a client device, a request for content identifying an account profile;
• determining, by the data processing system using a log record identifying a browsing history of the account profile, a first set of candidate languages from a plurality of languages by analyzing the log record using a language recognition model, wherein the language recognition model is trained according to a training dataset including corpuses of text for each language of the plurality of languages by:
• applying each of the corpuses of text for each language of the plurality of languages to the training dataset to generate a set of results corresponding to result languages of the plurality of languages,
• generating a result error by comparing each of the result languages to a labeled language for each of the corpuses, and
• modifying one or more weights of the language recognition model based on the result error;
• determining, by the data processing system, a second set of candidate languages from the plurality of languages based on a language setting of the account profile;
• identifying, by the data processing system, a set of languages included in both the first set of candidate languages and the second set of candidate languages, the set of languages including a first language and a second language from the plurality of the languages;
• and
• storing, by the data processing system in one or more data structures, an association among the account profile, the first language, and the second language.