End-to-end email tag prediction

A method of automatically generating end-to-end email tags in an email system, the method comprising:

• receiving email information from a first email client, wherein the email information is associated with an email message to be sent from the first email client to a second email client;
• generating a set of predicted tags from a set of available tags for the email message using a model;
• sending, by the email server, the set of predicted tags to the first email client to be appended to the email message;
• receiving the email message, a set of user tags, a set of unselected tags, and a set of selected tags from the first email client as the email message is sent to the second email client, wherein:
• the set of selected tags were selected from the set of predicted tags by a user;
• the set of unselected tags were not selected by from the set of predicted tags;
• and the set of user tags were provided by the user instead of being selected from the set of predicted tags;
• and
• retraining the model based on the set of selected tags, the set of unselected tags, and the set of user tags.

A system comprising:

• one or more processors;
• and
• one or more memory devices comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving email information from a first email client, wherein the email information is associated with an email message to be sent from the first email client to a second email client;
• generating a set of predicted tags from a set of available tags for the email message using a model;
• sending, by the email server, the set of predicted tags to the first email client to be appended to the email message;
• receiving the email message, a set of user tags, a set of unselected tags, and a set of selected tags from the first email client as the email message is sent to the second email client, wherein:
• the set of selected tags were selected from the set of predicted tags by a user;
• the set of unselected tags were not slected by from the set of predicted tags;
• and the set of user tags were provided by the user instead of being selected from the set of predicted tags;
• and
• retraining the model based on the set of selected tags, the set of unselected tags, and the set of user tags.