Transfer learning for seniority modeling label shortage

A system comprising:

• at least one hardware processor;
• and
• a non-transitory machine-readable medium embodying a set of instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations, the operations comprising:
• select a first plurality of reference users and a second plurality of reference users;
• filter out inactive users from the first plurality of reference users or the second plurality of reference users based on interaction data stored in a database;
• train an initialized neural network using a first plurality of training examples, the first plurality of training examples comprising profile data of the first plurality of reference users of an online service and a label for the profile data of each reference user in the first plurality of reference users, the label for the first profile data comprising a standardized position title, the training of the initialized neural network forming a pre-trained neural network;
• train the pre-trained neural network using a second plurality of training examples, the second plurality of training examples comprising profile data of the second plurality of reference users of the online service and a label for the second profile data of each reference user in the second plurality of reference users, the label for the second profile data comprising a position seniority, the training of the pre-trained neural network forming a fine-tuned neural network;
• compute the position seniority for a first target user of the online service based on profile data of the first target user using the fine-tuned neural network;
• use the position seniority of the first target user in an application of the online service to select a content item;
• and
• display, on a user interface of a computing device, the content item.

A non-transitory machine-readable medium embodying a set of instructions that, when executed by at least one hardware processor, cause the at least one hardware processor to perform operations, the operations comprising:

• select a first plurality of reference users and a second plurality of reference users;
• filter out inactive users from the first plurality of reference users or the second plurality of reference users based on interaction data stored in a database;
• train an initialized neural network using a first plurality of training examples, the first plurality of training examples comprising profile data of the first plurality of reference users of an online service and a label for the first profile data of each reference user in the first plurality of reference users, the label for the first profile data comprising a standardized position title, the training of the initialized neural network forming a pre-trained neural network;
• train the pre-trained neural network using a second plurality of training examples, the second plurality of training examples comprising profile data of the second plurality of reference users of the online service and a label for the second profile data of each reference user in the second plurality of reference users, the label for the second profile data of each reference user comprising a position seniority, the training of the pre-trained neural network forming a fine-tuned neural network;
• compute the position seniority for a first target user of the online service based on profile data of the first target user using the fine-tuned neural network;
• use the position seniority of the first target user in an application of the online service to select a content item;
• and
• display, on a user interface of a computing device, the content item.